PGLS analysis
Tia Harrison
2022-01-10
Overall setup
Global setup, load relevant packages
Dataset
Ploidy dataset and phylogeny
The spreadsheet contains information about the symbiotic status (Fixer column) of each legume species where 1 indicates a legume that forms nodules with rhizobia (symbiotic) and where 0 indicates a plant that forms no association with rhizobia (nonsymbiotic). The diPloidyLow column indicates whether plant species are diploids (coded as 0) or polyploid (coded as 1). The diPloidyLow values were calculated from genus-level data. The Num_Introduced column indicates how many separate ranges a plant species has been introduced to as calculated in Simonsen et al (2017).
The phylogeny used in this analysis is a version of the Zanne et al (2014) angiosperm phylogeny where the full phylogeny was pruned for the species in our dataset.
# Dataset
ploidy<- read.csv("Legume_ploidy_dataset.csv", row.names=1)
# Phylogeny
legumes1<-read.tree("Vascular_Plants_rooted.dated.tre")Clean up the dataset
Here, we create a new column called “NewPloidy” which indicates diploidy (0) and polyploidy (1) but was calculated from a combination of genus and subfamily level data.
We also added symbiotic species to our Fixer column if we had data from Harrison et al. (2018) that suggested those species associated with a rhizobium genus or OTU.
# If diPloidyLow (genus-level ploidy) is available use it and if not then use disfPloidy_corrected (subfamily with some species double checked in the literature)
# If there is data for NumGenera or OTUs then call the associating legume species a fixer
ploidy1<-ploidy%>%
rownames_to_column() %>%
mutate(NewPloidy = ifelse(is.na(diPloidyLow), disfPloidy_corrected, diPloidyLow)) %>%
mutate(Fixer = ifelse(is.na(Fixer) & numOTUs >= 1, 1, Fixer)) %>%
mutate(Fixer = ifelse(is.na(Fixer) & numGenera >=1 , 1, Fixer)) %>%
column_to_rownames()Prune the dataset and tree
# Make sure the data and tree match up
TreeOnly <- setdiff(legumes1$tip.label, rownames(ploidy1))
DataOnly <- setdiff(rownames(ploidy1), legumes1$tip.label)
# Prune the tree
pruned <- drop.tip(legumes1, TreeOnly)
pruned$node.label <- NULL
# Get the tip names
tip_names<-data.frame(pruned$tip.label)
# Filter the dataset for tree species
ploidy_data<-ploidy1 %>%
filter(rownames(ploidy1) %in% tip_names$pruned.tip.label)
# Set columns as factors for analysis
# Set Species as its own column
ploidy_data1 <- ploidy_data %>%
rownames_to_column("Species") %>%
mutate(Fixer=as.factor(Fixer),
numGenera=as.factor(numGenera),
Specialist=as.factor(Specialist),
diPloidyLow=as.factor(diPloidyLow),
NewPloidy=as.factor(NewPloidy))Data exploration
How many species in each data type?
# Data summary for genus level ploidy
ploidy_data1 %>%
filter(!is.na(diPloidyLow) & !is.na(Num_Introduced) & !is.na(Fixer)) %>%
group_by(diPloidyLow, Fixer) %>%
tally()## # A tibble: 4 × 3
## # Groups: diPloidyLow [2]
## diPloidyLow Fixer n
## <fct> <fct> <int>
## 1 0 0 21
## 2 0 1 412
## 3 1 0 2
## 4 1 1 229# Average of introduced ranges
ploidy_data1 %>%
filter(!is.na(diPloidyLow) & !is.na(Num_Introduced) & !is.na(Fixer)) %>%
group_by(diPloidyLow, Fixer) %>%
summarize(mean(Num_Introduced))## `summarise()` has grouped output by 'diPloidyLow'. You can override using the `.groups` argument.## # A tibble: 4 × 3
## # Groups: diPloidyLow [2]
## diPloidyLow Fixer `mean(Num_Introduced)`
## <fct> <fct> <dbl>
## 1 0 0 7.43
## 2 0 1 5.67
## 3 1 0 32
## 4 1 1 4.09# What are the two non-symbiotic polyploid species?
ploidy_data1 %>%
filter(diPloidyLow==1 & Fixer ==0)## Species Genus areaIntroduced areaIntroducedScale areaNative
## 1 Cassia_fistula Cassia 3.90e+13 4.6741299 1.02e+13
## 2 Cassia_grandis Cassia 9.33e+12 0.8603899 1.27e+13
## areaNativeScale Num_Introduced Fixer numOTUs numGenera Specialist Human_Uses
## 1 0.4054753 47 0 NA <NA> <NA> 7
## 2 0.7269305 17 0 NA <NA> <NA> 4
## AbsLatNative LatNative ChromosomeCount PloidyLow diPloidyLow sfPloidy
## 1 10.689225 10.689225 28 4 1 4
## 2 2.346186 2.346186 28 4 1 4
## disfPloidy annual disfPloidy_corrected NewPloidy
## 1 1 0 1 1
## 2 1 0 1 1# Cassia fistula 7 human uses
# Cassia grandis 4 human uses
# Average number of human uses
ploidy_data1 %>%
filter(!is.na(Fixer) & !is.na(Human_Uses)) %>%
group_by(Fixer) %>%
summarize(mean(Human_Uses))## # A tibble: 2 × 2
## Fixer `mean(Human_Uses)`
## <fct> <dbl>
## 1 0 2.90
## 2 1 1.43# Data summary for subfamily level ploidy data
ploidy_data1 %>%
filter(!is.na(NewPloidy) & !is.na(Num_Introduced) & !is.na(Fixer)) %>%
group_by(NewPloidy, Fixer) %>%
tally()## # A tibble: 4 × 3
## # Groups: NewPloidy [2]
## NewPloidy Fixer n
## <fct> <fct> <int>
## 1 0 0 42
## 2 0 1 515
## 3 1 0 26
## 4 1 1 256# Average number of human uses in specialists
ploidy_data1 %>%
filter(!is.na(Specialist) & !is.na(Human_Uses) & !is.na(NewPloidy)) %>%
group_by(Specialist, NewPloidy) %>%
summarize(mean(Human_Uses))## `summarise()` has grouped output by 'Specialist'. You can override using the `.groups` argument.## # A tibble: 4 × 3
## # Groups: Specialist [2]
## Specialist NewPloidy `mean(Human_Uses)`
## <fct> <fct> <dbl>
## 1 0 0 3.57
## 2 0 1 4.29
## 3 1 0 2.94
## 4 1 1 3.4Comparison of genus level and genus+subfamily data
Here we looked at the species added in the genus+subfamily dataset in terms of fixer status and number of introduced ranges.
add_spp<- ploidy_data1 %>%
filter(!is.na(NewPloidy) & is.na(diPloidyLow) & !is.na(Num_Introduced) & !is.na(Fixer))
add_spp %>%
group_by(Fixer, NewPloidy) %>%
tally()## # A tibble: 4 × 3
## # Groups: Fixer [2]
## Fixer NewPloidy n
## <fct> <fct> <int>
## 1 0 0 21
## 2 0 1 24
## 3 1 0 103
## 4 1 1 27add_spp %>%
group_by(Fixer, NewPloidy) %>%
summarize(mean(Num_Introduced))## `summarise()` has grouped output by 'Fixer'. You can override using the `.groups` argument.## # A tibble: 4 × 3
## # Groups: Fixer [2]
## Fixer NewPloidy `mean(Num_Introduced)`
## <fct> <fct> <dbl>
## 1 0 0 6.95
## 2 0 1 12.3
## 3 1 0 2.17
## 4 1 1 3.07# Average number of ranges in the species that are based on subfamily values
add_spp %>%
filter(is.na(diPloidyLow) & !is.na(disfPloidy_corrected)) %>%
summarize(mean(Num_Introduced)) # 4.2742 ## mean(Num_Introduced)
## 1 4.274286# Average number of ranges in the species that are based on genus values
ploidy_data1 %>%
filter(!is.na(NewPloidy) & !is.na(diPloidyLow) & !is.na(Fixer) & !is.na(Num_Introduced)) %>%
summarize(mean(Num_Introduced)) # 5.262048## mean(Num_Introduced)
## 1 5.262048Data analysis
Correlation tests
We looked at the correlation between subfamily base chromosome number and genus base chromosome number to determine how similar our two datasets are.
# Spearman's rank correlation
# Ties present so we didn't compute exact p value
cor.test(ploidy_data1$PloidyLow, ploidy_data1$sfPloidy, method="spearman", exact=FALSE)##
## Spearman's rank correlation rho
##
## data: ploidy_data1$PloidyLow and ploidy_data1$sfPloidy
## S = 25887790, p-value < 2.2e-16
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.4694297# Kendall tau correlation to deal with ties
cor.test(ploidy_data1$PloidyLow, ploidy_data1$sfPloidy, method="kendall")##
## Kendall's rank correlation tau
##
## data: ploidy_data1$PloidyLow and ploidy_data1$sfPloidy
## z = 11.989, p-value < 2.2e-16
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.4126668PGLS on the genus + subfamily level ploidy data
We performed our anlayses on the genus + subfamily dataset since it had the most data points in each category of data (diploid non-symbiotic, diploid symbiotic, polyploid non-symbiotic, and polyploid symbiotic). We tested the hypothesis that ploidy and symbiotic status or rhizobia specificity interact to impact range expansion using pgls models with the nlme package.
In the PGLS model if you are having trouble getting the model to converge try setting different values for lambda (0, 1, or 0.5). If changing lambda doesn’t work try this code to get convergence in the model: control=glsControl(opt=“optim”,optimMethod=“Nelder-Mead”)
# Run pgls and allow lambda to vary in symbiotic status
model_sub2<-gls(log10(Num_Introduced+1) ~ NewPloidy*Fixer + AbsLatNative + areaNativeScale + Human_Uses + annual, data=ploidy_data1, correlation=corPagel(value=0, phy=pruned, fixed=FALSE, form=~"Species"), method = "ML", na.action=na.exclude)
# Inspect model fit
plot(model_sub2)
qqnorm(resid(model_sub2))
qqline(resid(model_sub2))
# Test for significance
summary(model_sub2)## Generalized least squares fit by maximum likelihood
## Model: log10(Num_Introduced + 1) ~ NewPloidy * Fixer + AbsLatNative + areaNativeScale + Human_Uses + annual
## Data: ploidy_data1
## AIC BIC logLik
## 654.9941 701.9768 -317.4971
##
## Correlation Structure: corPagel
## Formula: ~"Species"
## Parameter estimate(s):
## lambda
## 0.04424329
##
## Coefficients:
## Value Std.Error t-value p-value
## (Intercept) 0.14718037 0.07306654 2.014333 0.0443
## NewPloidy1 0.12862245 0.09270510 1.387437 0.1657
## Fixer1 0.00204796 0.06006921 0.034093 0.9728
## AbsLatNative -0.00218817 0.00093790 -2.333055 0.0199
## areaNativeScale -0.04197123 0.01194299 -3.514299 0.0005
## Human_Uses 0.18777460 0.00687942 27.295120 0.0000
## annual 0.07353937 0.03344086 2.199087 0.0282
## NewPloidy1:Fixer1 -0.11777689 0.09719271 -1.211787 0.2260
##
## Correlation:
## (Intr) NwPld1 Fixer1 AbsLtN arNtvS Hmn_Us annual
## NewPloidy1 -0.469
## Fixer1 -0.753 0.561
## AbsLatNative -0.250 0.058 -0.094
## areaNativeScale 0.045 0.013 -0.056 0.111
## Human_Uses -0.259 -0.053 0.108 0.076 -0.366
## annual -0.011 0.016 -0.042 -0.093 -0.034 0.078
## NewPloidy1:Fixer1 0.456 -0.952 -0.575 -0.077 -0.023 0.068 -0.032
##
## Standardized residuals:
## Min Q1 Med Q3 Max
## -3.1933995 -0.4802500 -0.2610835 0.5827916 3.2760135
##
## Residual standard error: 0.3616302
## Degrees of freedom: 811 total; 803 residualAnova(model_sub2, contrasts=list(topic=contr.sum, sys=contr.sum), type=3) # Type 3 for interaction and contrasts set ## Analysis of Deviance Table (Type III tests)
##
## Response: log10(Num_Introduced + 1)
## Df Chisq Pr(>Chisq)
## (Intercept) 1 4.0575 0.0439745 *
## NewPloidy 1 1.9250 0.1653087
## Fixer 1 0.0012 0.9728027
## AbsLatNative 1 5.4431 0.0196453 *
## areaNativeScale 1 12.3503 0.0004409 ***
## Human_Uses 1 745.0236 < 2.2e-16 ***
## annual 1 4.8360 0.0278717 *
## NewPloidy:Fixer 1 1.4684 0.2255938
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Ploidy estimates have the expected sign, interaction is non-significant, but fixer estimate is opposite to what is expected
# Get means from the model
model_sub2_results<-lsmeans(model_sub2, pairwise~NewPloidy+Fixer, mode = "df.error")
model_sub2_results<-data.frame(model_sub2_results$lsmeans)
#Lambda is negative, so no phylogenetic clustering of trait
#Therefore compare to a phylogenetically uncorrected model
#Let's start with a Poisson model
model_poisson <- glm(Num_Introduced ~ NewPloidy*Fixer + AbsLatNative + areaNativeScale + Human_Uses + annual, data=ploidy_data1, family="poisson")
#Inspect model fit
plot(model_poisson) #Fit isn't awesome
qqnorm(resid(model_poisson))
qqline(resid(model_poisson))
summary(model_poisson) #Probably not correct because of over-dispersion##
## Call:
## glm(formula = Num_Introduced ~ NewPloidy * Fixer + AbsLatNative +
## areaNativeScale + Human_Uses + annual, family = "poisson",
## data = ploidy_data1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -8.6505 -1.9724 -1.6309 0.2977 12.3472
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.403115 0.069960 5.762 8.31e-09 ***
## NewPloidy1 0.531661 0.078600 6.764 1.34e-11 ***
## Fixer1 0.268504 0.062130 4.322 1.55e-05 ***
## AbsLatNative -0.010771 0.001115 -9.658 < 2e-16 ***
## areaNativeScale -0.120011 0.011944 -10.048 < 2e-16 ***
## Human_Uses 0.430389 0.005847 73.603 < 2e-16 ***
## annual 0.404416 0.039917 10.131 < 2e-16 ***
## NewPloidy1:Fixer1 -0.634903 0.087161 -7.284 3.23e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 10821.6 on 810 degrees of freedom
## Residual deviance: 5151.9 on 803 degrees of freedom
## (54 observations deleted due to missingness)
## AIC: 6577.9
##
## Number of Fisher Scoring iterations: 6coeftest(model_poisson, vcov = sandwich) #Recompute Wald tests using sandwich standard errors, and it's likely more correct##
## z test of coefficients:
##
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.4031152 0.2156317 1.8695 0.061559 .
## NewPloidy1 0.5316608 0.2209895 2.4058 0.016136 *
## Fixer1 0.2685044 0.1925074 1.3948 0.163084
## AbsLatNative -0.0107713 0.0036823 -2.9252 0.003443 **
## areaNativeScale -0.1200108 0.0404212 -2.9690 0.002988 **
## Human_Uses 0.4303892 0.0176316 24.4101 < 2.2e-16 ***
## annual 0.4044161 0.1367858 2.9566 0.003111 **
## NewPloidy1:Fixer1 -0.6349034 0.2511534 -2.5280 0.011473 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#Quasipoisson model for number of introductions is probably preferrable given over-dispersion
model_qpoisson <-glm(Num_Introduced ~ NewPloidy*Fixer + AbsLatNative + areaNativeScale + Human_Uses + annual, data=ploidy_data1, family="quasipoisson")
#Inspect model fit
plot(model_qpoisson) #Fit isn't awesome
qqnorm(resid(model_qpoisson))
qqline(resid(model_qpoisson))
summary(model_qpoisson)##
## Call:
## glm(formula = Num_Introduced ~ NewPloidy * Fixer + AbsLatNative +
## areaNativeScale + Human_Uses + annual, family = "quasipoisson",
## data = ploidy_data1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -8.6505 -1.9724 -1.6309 0.2977 12.3472
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.403115 0.198575 2.030 0.042682 *
## NewPloidy1 0.531661 0.223099 2.383 0.017400 *
## Fixer1 0.268504 0.176350 1.523 0.128261
## AbsLatNative -0.010771 0.003166 -3.403 0.000700 ***
## areaNativeScale -0.120011 0.033902 -3.540 0.000423 ***
## Human_Uses 0.430389 0.016597 25.931 < 2e-16 ***
## annual 0.404416 0.113302 3.569 0.000379 ***
## NewPloidy1:Fixer1 -0.634903 0.247398 -2.566 0.010459 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for quasipoisson family taken to be 8.056593)
##
## Null deviance: 10821.6 on 810 degrees of freedom
## Residual deviance: 5151.9 on 803 degrees of freedom
## (54 observations deleted due to missingness)
## AIC: NA
##
## Number of Fisher Scoring iterations: 6coeftest(model_qpoisson, vcov = sandwich) ##
## z test of coefficients:
##
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.4031152 0.2156317 1.8695 0.061559 .
## NewPloidy1 0.5316608 0.2209895 2.4058 0.016136 *
## Fixer1 0.2685044 0.1925074 1.3948 0.163084
## AbsLatNative -0.0107713 0.0036823 -2.9252 0.003443 **
## areaNativeScale -0.1200108 0.0404212 -2.9690 0.002988 **
## Human_Uses 0.4303892 0.0176316 24.4101 < 2.2e-16 ***
## annual 0.4044161 0.1367858 2.9566 0.003111 **
## NewPloidy1:Fixer1 -0.6349034 0.2511534 -2.5280 0.011473 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Anova(model_qpoisson, contrasts=list(topic=contr.sum, sys=contr.sum), type=3)## Analysis of Deviance Table (Type III tests)
##
## Response: Num_Introduced
## LR Chisq Df Pr(>Chisq)
## NewPloidy 5.70 1 0.0169598 *
## Fixer 2.47 1 0.1158945
## AbsLatNative 11.71 1 0.0006232 ***
## areaNativeScale 13.44 1 0.0002468 ***
## Human_Uses 592.01 1 < 2.2e-16 ***
## annual 11.92 1 0.0005565 ***
## NewPloidy:Fixer 6.63 1 0.0100457 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Run pgls for specificity on rhizobia
model_sub_spec2<-gls(log10(Num_Introduced+1) ~ NewPloidy*Specialist + AbsLatNative + areaNativeScale + Human_Uses + annual, data=ploidy_data1, correlation=corPagel(value=0, phy=pruned, fixed=FALSE, form=~"Species"), method = "ML", na.action=na.exclude, control=glsControl(opt="optim",optimMethod="Nelder-Mead"))## Warning in optim(c(coef(glsSt)), function(glsPars) -logLik(glsSt, glsPars), : one-dimensional optimization by Nelder-Mead is unreliable:
## use "Brent" or optimize() directly# Inspect model fit
plot(model_sub_spec2)
qqnorm(resid(model_sub_spec2))
qqline(resid(model_sub_spec2))
# Test for significance
summary(model_sub_spec2)## Generalized least squares fit by maximum likelihood
## Model: log10(Num_Introduced + 1) ~ NewPloidy * Specialist + AbsLatNative + areaNativeScale + Human_Uses + annual
## Data: ploidy_data1
## AIC BIC logLik
## 125.4096 154.0849 -52.70479
##
## Correlation Structure: corPagel
## Formula: ~"Species"
## Parameter estimate(s):
## lambda
## -0.1992188
##
## Coefficients:
## Value Std.Error t-value p-value
## (Intercept) 0.4000346 0.11142427 3.590193 0.0005
## NewPloidy1 0.4789848 0.17175214 2.788814 0.0061
## Specialist1 0.1678036 0.08716170 1.925199 0.0565
## AbsLatNative -0.0118812 0.00231142 -5.140226 0.0000
## areaNativeScale -0.1164701 0.02381255 -4.891124 0.0000
## Human_Uses 0.1725507 0.01541866 11.191030 0.0000
## annual 0.0074739 0.09777208 0.076442 0.9392
## NewPloidy1:Specialist1 -0.5298943 0.19225704 -2.756176 0.0067
##
## Correlation:
## (Intr) NwPld1 Spcls1 AbsLtN arNtvS Hmn_Us annual
## NewPloidy1 -0.270
## Specialist1 -0.624 0.416
## AbsLatNative -0.655 -0.174 0.099
## areaNativeScale -0.192 -0.143 -0.023 0.265
## Human_Uses -0.536 0.017 0.110 0.134 -0.272
## annual -0.242 -0.065 0.036 0.094 0.075 0.018
## NewPloidy1:Specialist1 0.269 -0.869 -0.546 0.177 0.138 -0.010 0.065
##
## Standardized residuals:
## Min Q1 Med Q3 Max
## -3.1396684 -0.4907200 0.3693319 1.0901147 3.0033505
##
## Residual standard error: 0.3662198
## Degrees of freedom: 130 total; 122 residualAnova(model_sub_spec2, contrasts=list(topic=contr.sum), type=3)## Analysis of Deviance Table (Type III tests)
##
## Response: log10(Num_Introduced + 1)
## Df Chisq Pr(>Chisq)
## (Intercept) 1 12.8895 0.0003304 ***
## NewPloidy 1 7.7775 0.0052901 **
## Specialist 1 3.7064 0.0542045 .
## AbsLatNative 1 26.4219 2.744e-07 ***
## areaNativeScale 1 23.9231 1.003e-06 ***
## Human_Uses 1 125.2392 < 2.2e-16 ***
## annual 1 0.0058 0.9390675
## NewPloidy:Specialist 1 7.5965 0.0058481 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Ploidy estimate sign is correct, specialist estimate is opposite sign as to what expected, interaction is significant
# Grab the model means
model_sub_spec2_results<-lsmeans(model_sub_spec2, pairwise~NewPloidy+Specialist, mode = "df.error")
model_sub_spec2_results<-data.frame(model_sub_spec2_results$lsmeans)
#Fit Poisson model for specificity
model_spec_poisson <- glm(Num_Introduced ~ NewPloidy*Specialist + AbsLatNative + areaNativeScale + Human_Uses + annual, data=ploidy_data1, family="poisson")
#Inspect model fit
plot(model_spec_poisson) #Fit isn't terrible
qqnorm(resid(model_spec_poisson))
qqline(resid(model_spec_poisson))
summary(model_spec_poisson) ##
## Call:
## glm(formula = Num_Introduced ~ NewPloidy * Specialist + AbsLatNative +
## areaNativeScale + Human_Uses + annual, family = "poisson",
## data = ploidy_data1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -8.7162 -2.8554 -0.8980 0.8747 9.9823
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.945549 0.078400 24.816 < 2e-16 ***
## NewPloidy1 0.498004 0.085805 5.804 6.48e-09 ***
## Specialist1 0.115956 0.056597 2.049 0.0405 *
## AbsLatNative -0.020266 0.001624 -12.480 < 2e-16 ***
## areaNativeScale -0.220055 0.015883 -13.854 < 2e-16 ***
## Human_Uses 0.290491 0.009940 29.224 < 2e-16 ***
## annual 0.238563 0.055540 4.295 1.74e-05 ***
## NewPloidy1:Specialist1 -0.930729 0.112206 -8.295 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 2517 on 129 degrees of freedom
## Residual deviance: 1193 on 122 degrees of freedom
## (735 observations deleted due to missingness)
## AIC: 1627.7
##
## Number of Fisher Scoring iterations: 5coeftest(model_spec_poisson, vcov = sandwich) #Recompute Wald tests using sandwich standard errors, and it's likely more correct##
## z test of coefficients:
##
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.9455492 0.2312515 8.4131 < 2.2e-16 ***
## NewPloidy1 0.4980043 0.2516343 1.9791 0.047807 *
## Specialist1 0.1159561 0.1777887 0.6522 0.514264
## AbsLatNative -0.0202660 0.0045768 -4.4280 9.511e-06 ***
## areaNativeScale -0.2200550 0.0435145 -5.0570 4.258e-07 ***
## Human_Uses 0.2904914 0.0296879 9.7849 < 2.2e-16 ***
## annual 0.2385632 0.1656679 1.4400 0.149865
## NewPloidy1:Specialist1 -0.9307286 0.3123907 -2.9794 0.002888 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#Quasipoisson model for number of introductions is probably preferrable given over-dispersion
model_spec_qpoisson <-glm(Num_Introduced ~ NewPloidy*Specialist + AbsLatNative + areaNativeScale + Human_Uses + annual, data=ploidy_data1, family="quasipoisson")
#Inspect model fit
plot(model_spec_qpoisson) 
qqnorm(resid(model_spec_qpoisson))
qqline(resid(model_spec_qpoisson))
summary(model_spec_qpoisson)##
## Call:
## glm(formula = Num_Introduced ~ NewPloidy * Specialist + AbsLatNative +
## areaNativeScale + Human_Uses + annual, family = "quasipoisson",
## data = ploidy_data1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -8.7162 -2.8554 -0.8980 0.8747 9.9823
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.945549 0.248660 7.824 2.07e-12 ***
## NewPloidy1 0.498004 0.272147 1.830 0.069705 .
## Specialist1 0.115956 0.179509 0.646 0.519516
## AbsLatNative -0.020266 0.005151 -3.935 0.000139 ***
## areaNativeScale -0.220055 0.050377 -4.368 2.65e-05 ***
## Human_Uses 0.290491 0.031528 9.214 1.13e-15 ***
## annual 0.238563 0.176156 1.354 0.178153
## NewPloidy1:Specialist1 -0.930729 0.355885 -2.615 0.010041 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for quasipoisson family taken to be 10.05968)
##
## Null deviance: 2517 on 129 degrees of freedom
## Residual deviance: 1193 on 122 degrees of freedom
## (735 observations deleted due to missingness)
## AIC: NA
##
## Number of Fisher Scoring iterations: 5coeftest(model_spec_qpoisson, vcov = sandwich) ##
## z test of coefficients:
##
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.9455492 0.2312515 8.4131 < 2.2e-16 ***
## NewPloidy1 0.4980043 0.2516343 1.9791 0.047807 *
## Specialist1 0.1159561 0.1777887 0.6522 0.514264
## AbsLatNative -0.0202660 0.0045768 -4.4280 9.511e-06 ***
## areaNativeScale -0.2200550 0.0435145 -5.0570 4.258e-07 ***
## Human_Uses 0.2904914 0.0296879 9.7849 < 2.2e-16 ***
## annual 0.2385632 0.1656679 1.4400 0.149865
## NewPloidy1:Specialist1 -0.9307286 0.3123907 -2.9794 0.002888 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Anova(model_spec_qpoisson, contrasts=list(topic=contr.sum, sys=contr.sum), type=3)## Analysis of Deviance Table (Type III tests)
##
## Response: Num_Introduced
## LR Chisq Df Pr(>Chisq)
## NewPloidy 3.114 1 0.07762 .
## Specialist 0.420 1 0.51673
## AbsLatNative 15.868 1 6.793e-05 ***
## areaNativeScale 22.078 1 2.618e-06 ***
## Human_Uses 89.031 1 < 2.2e-16 ***
## annual 1.764 1 0.18408
## NewPloidy:Specialist 6.640 1 0.00997 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Analyzing the non-symbiotic and symbiotic species separately
Here we subset the data to only the non-symbiotic species in the combined genus+subfamily dataset to look for an effect of ploidy on invasion.
# Subset the data to non-symbiotic species
ploidy_data_non <- ploidy_data1 %>%
filter(Fixer == 0)
ploidy_data_non # Reduces the dataset to 68 species and two categories (diploid and polyploid)## Species Genus areaIntroduced
## 1 Acacia_bonariensis Acacia 0.000000e+00
## 2 Acacia_greggii Acacia 2.060000e+12
## 3 Acrocarpus_fraxinifolius Acrocarpus 6.430000e+12
## 4 Amburana_cearensis Amburana 0.000000e+00
## 5 Apuleia_leiocarpa Apuleia 0.000000e+00
## 6 Bauhinia_forficata Bauhinia 7.761980e+08
## 7 Bauhinia_galpinii Bauhinia 4.960000e+12
## 8 Bauhinia_monandra Bauhinia 9.760000e+12
## 9 Bauhinia_petersiana Bauhinia 8.243619e+10
## 10 Bauhinia_purpurea Bauhinia 2.230000e+13
## 11 Bauhinia_rufescens Bauhinia 2.880000e+12
## 12 Bauhinia_ungulata Bauhinia 3.285052e+08
## 13 Bauhinia_variegata Bauhinia 2.570000e+13
## 14 Caesalpinia_bonduc Caesalpinia 5.220000e+12
## 15 Caesalpinia_decapetala Caesalpinia 1.840000e+13
## 16 Caesalpinia_echinata Caesalpinia 0.000000e+00
## 17 Caesalpinia_paraguariensis Caesalpinia 0.000000e+00
## 18 Caesalpinia_pluviosa Caesalpinia 0.000000e+00
## 19 Caesalpinia_sappan Caesalpinia 1.830000e+13
## 20 Caesalpinia_spinosa Caesalpinia 5.920000e+12
## 21 Cassia_fistula Cassia 3.900000e+13
## 22 Cassia_grandis Cassia 9.330000e+12
## 23 Castanospermum_australe Castanospermum 8.870000e+12
## 24 Cercis_canadensis Cercis 3.650000e+12
## 25 Cercis_siliquastrum Cercis 1.500000e+13
## 26 Colvillea_racemosa Colvillea 3.680000e+12
## 27 Copaifera_langsdorffii Copaifera 0.000000e+00
## 28 Copaifera_officinalis Copaifera 3.790000e+11
## 29 Dalea_mollis Dalea 0.000000e+00
## 30 Delonix_elata Delonix 7.910000e+12
## 31 Dipteryx_odorata Dipteryx 2.891642e+07
## 32 Distemonanthus_benthamianus Distemonanthus 0.000000e+00
## 33 Gleditsia_amorphoides Gleditsia 3.330000e+12
## 34 Gleditsia_japonica Gleditsia 4.080000e+11
## 35 Gleditsia_triacanthos Gleditsia 2.910000e+13
## 36 Guibourtia_coleosperma Guibourtia 0.000000e+00
## 37 Gymnocladus_chinensis Gymnocladus 0.000000e+00
## 38 Gymnocladus_dioica Gymnocladus 1.330000e+13
## 39 Haematoxylum_campechianum Haematoxylum 2.040000e+13
## 40 Hoffmannseggia_glauca Hoffmannseggia 0.000000e+00
## 41 Hymenaea_courbaril Hymenaea 4.440000e+12
## 42 Hymenaea_parvifolia Hymenaea 0.000000e+00
## 43 Hymenaea_verrucosa Hymenaea 5.590000e+12
## 44 Hymenostegia_afzelii Hymenostegia 0.000000e+00
## 45 Maackia_hupehensis Maackia 0.000000e+00
## 46 Parkia_biglandulosa Parkia 2.870000e+12
## 47 Parkinsonia_aculeata Parkinsonia 4.250000e+13
## 48 Peltophorum_dubium Peltophorum 3.800000e+12
## 49 Peltophorum_pterocarpum Peltophorum 2.000000e+13
## 50 Petalostylis_labicheoides Petalostylis 0.000000e+00
## 51 Pickeringia_montana Pickeringia 0.000000e+00
## 52 Psorothamnus_fremontii Psorothamnus 0.000000e+00
## 53 Pterodon_emarginatus Pterodon 0.000000e+00
## 54 Pterogyne_nitens Pterogyne 8.240000e+11
## 55 Schizolobium_parahyba Schizolobium 1.100000e+13
## 56 Schotia_brachypetala Schotia 4.530000e+12
## 57 Senna_alexandrina Senna 2.020000e+12
## 58 Senna_candolleana Senna 0.000000e+00
## 59 Senna_didymobotrya Senna 6.790000e+12
## 60 Senna_obtusifolia Senna 3.750000e+13
## 61 Senna_occidentalis Senna 3.020000e+13
## 62 Senna_pendula Senna 7.030000e+12
## 63 Senna_reticulata Senna 0.000000e+00
## 64 Senna_surattensis Senna 8.970000e+12
## 65 Senna_tora Senna 9.940000e+12
## 66 Sindora_siamensis Sindora 0.000000e+00
## 67 Sindora_supa Sindora 0.000000e+00
## 68 Tamarindus_indica Tamarindus 4.370000e+13
## areaIntroducedScale areaNative areaNativeScale Num_Introduced Fixer numOTUs
## 1 -0.33887512 4.27e+12 -0.35701649 0 0 NA
## 2 -0.07408562 2.28e+12 -0.61289484 1 0 NA
## 3 0.48762802 8.76e+12 0.22031709 5 0 NA
## 4 -0.33887512 NA NA 0 0 NA
## 5 -0.33887512 1.46e+13 0.97123649 0 0 NA
## 6 -0.33877535 1.40e+13 0.89408724 1 0 NA
## 7 0.29867629 3.86e+12 -0.40973514 15 0 NA
## 8 0.91566152 5.93e+11 -0.82981283 15 0 NA
## 9 -0.32827889 1.06e+13 0.45690814 1 0 NA
## 10 2.52753545 1.71e+13 1.29269172 29 0 NA
## 11 0.03131602 9.90e+12 0.36690068 4 0 NA
## 12 -0.33883290 1.07e+13 0.46976635 1 0 NA
## 13 2.96456666 1.48e+13 0.99695291 27 0 NA
## 14 0.33209632 3.00e+13 2.95140066 5 0 NA
## 15 2.02623495 1.55e+13 1.08696037 14 0 NA
## 16 -0.33887512 8.47e+12 0.18302829 0 0 NA
## 17 -0.33887512 4.27e+12 -0.35701649 0 0 NA
## 18 -0.33887512 8.47e+12 0.18302829 0 0 NA
## 19 2.01338109 8.04e+12 0.12773799 20 0 NA
## 20 0.42207334 5.91e+12 -0.14614186 7 0 NA
## 21 4.67412991 1.02e+13 0.40547530 47 0 NA
## 22 0.86038993 1.27e+13 0.72693052 17 0 NA
## 23 0.80126218 2.69e+12 -0.56017619 15 0 NA
## 24 0.13029073 1.43e+13 0.93266187 5 0 NA
## 25 1.58920374 5.14e+12 -0.24515007 21 0 NA
## 26 0.13414689 5.93e+11 -0.82981283 12 0 NA
## 27 -0.33887512 6.13e+12 -0.11785380 0 0 NA
## 28 -0.29015899 3.05e+12 -0.51388663 5 0 NA
## 29 -0.33887512 7.02e+11 -0.81579738 0 0 NA
## 30 0.67786513 1.23e+13 0.67549769 12 0 NA
## 31 -0.33887140 6.95e+12 -0.01241649 1 0 NA
## 32 -0.33887512 2.45e+12 -0.59103589 0 0 NA
## 33 0.08915839 1.18e+13 0.61120664 3 0 NA
## 34 -0.28643137 2.52e+12 -0.58203514 1 0 NA
## 35 3.40159786 1.52e+13 1.04838575 25 0 NA
## 36 -0.33887512 6.09e+12 -0.12299708 0 0 NA
## 37 -0.33887512 1.83e+12 -0.67075678 0 0 NA
## 38 1.37068813 1.63e+13 1.18982604 9 0 NA
## 39 2.28331213 2.44e+12 -0.59232171 31 0 NA
## 40 -0.33887512 9.16e+12 0.27174993 0 0 NA
## 41 0.23183622 4.84e+12 -0.28372470 11 0 NA
## 42 -0.33887512 1.29e+13 0.75264694 0 0 NA
## 43 0.37965560 5.10e+12 -0.25029335 12 0 NA
## 44 -0.33887512 2.40e+12 -0.59746499 0 0 NA
## 45 -0.33887512 1.75e+12 -0.68104335 0 0 NA
## 46 0.03003063 8.07e+11 -0.80229626 10 0 NA
## 47 5.12401498 1.76e+13 1.35698276 26 0 NA
## 48 0.14957152 1.18e+13 0.61120664 6 0 NA
## 49 2.23189669 8.83e+12 0.22931784 32 0 NA
## 50 -0.33887512 6.04e+12 -0.12942619 0 0 NA
## 51 -0.33887512 4.74e+11 -0.84511410 0 0 NA
## 52 -0.33887512 1.21e+12 -0.75047768 0 0 NA
## 53 -0.33887512 4.66e+12 -0.30686947 0 0 NA
## 54 -0.23295932 1.05e+13 0.44404993 1 0 NA
## 55 1.07504938 9.85e+12 0.36047157 10 0 NA
## 56 0.24340470 3.86e+12 -0.40973514 5 0 NA
## 57 -0.07922717 1.91e+13 1.54985589 9 0 NA
## 58 -0.33887512 NA NA 0 0 NA
## 59 0.53390191 1.12e+13 0.53405739 20 0 NA
## 60 4.48132203 2.06e+12 -0.64118290 20 0 NA
## 61 3.54299031 2.75e+13 2.62994544 48 0 NA
## 62 0.56475117 1.31e+11 -0.88921775 7 0 NA
## 63 -0.33887512 1.42e+13 0.91980366 0 0 NA
## 64 0.81411604 1.71e+13 1.29269172 27 0 NA
## 65 0.93879847 1.46e+13 0.97123649 19 0 NA
## 66 -0.33887512 4.17e+12 -0.36987469 0 0 NA
## 67 -0.33887512 2.02e+12 -0.64632619 0 0 NA
## 68 5.27826129 2.04e+13 1.71701261 49 0 NA
## numGenera Specialist Human_Uses AbsLatNative LatNative ChromosomeCount
## 1 <NA> <NA> 0 26.9470519 -26.9470519 26
## 2 <NA> <NA> 1 27.1950111 27.1950111 26
## 3 <NA> <NA> 2 17.3649915 17.3649915 24
## 4 <NA> <NA> 0 NA NA 22
## 5 <NA> <NA> 0 4.5631422 -4.5631422 28
## 6 <NA> <NA> 0 15.9895911 -15.9895911 28
## 7 <NA> <NA> 1 21.7294751 -21.7294751 28
## 8 <NA> <NA> 1 19.3735274 -19.3735274 28
## 9 <NA> <NA> 0 18.5853378 -18.5853378 26
## 10 <NA> <NA> 9 22.9386032 22.9386032 28
## 11 <NA> <NA> 6 14.3408522 14.3408522 23
## 12 <NA> <NA> 0 7.8624843 -7.8624843 28
## 13 <NA> <NA> 6 24.0086267 24.0086267 28
## 14 <NA> <NA> 4 6.2806233 6.2806233 24
## 15 <NA> <NA> 5 16.7971417 16.7971417 22
## 16 <NA> <NA> 0 10.7722795 -10.7722795 24
## 17 <NA> <NA> 1 26.9470519 -26.9470519 24
## 18 <NA> <NA> 0 10.7722795 -10.7722795 24
## 19 <NA> <NA> 6 9.4601436 9.4601436 24
## 20 <NA> <NA> 2 10.2682571 -10.2682571 24
## 21 <NA> <NA> 7 10.6892249 10.6892249 28
## 22 <NA> <NA> 4 2.3461862 2.3461862 28
## 23 <NA> <NA> 5 17.6442593 -17.6442593 26
## 24 <NA> <NA> 3 34.0843962 34.0843962 12
## 25 <NA> <NA> 4 39.4039814 39.4039814 14
## 26 <NA> <NA> 2 19.3735274 -19.3735274 27
## 27 <NA> <NA> 0 16.7355339 -16.7355339 24
## 28 <NA> <NA> 5 5.6211657 5.6211657 24
## 29 <NA> <NA> 0 36.0327801 36.0327801 16
## 30 <NA> <NA> 5 15.1395972 15.1395972 28
## 31 <NA> <NA> 7 2.8627333 -2.8627333 32
## 32 <NA> <NA> 3 7.6159951 7.6159951 24
## 33 <NA> <NA> 0 24.5855168 -24.5855168 28
## 34 <NA> <NA> 5 35.8532940 35.8532940 28
## 35 <NA> <NA> 7 41.0748998 41.0748998 28
## 36 <NA> <NA> 4 11.7395381 -11.7395381 48
## 37 <NA> <NA> 2 27.6064912 27.6064912 28
## 38 <NA> <NA> 4 54.1279384 54.1279384 28
## 39 <NA> <NA> 5 19.2976685 19.2976685 24
## 40 <NA> <NA> 0 3.5130894 3.5130894 24
## 41 <NA> <NA> 3 9.2242963 9.2242963 24
## 42 <NA> <NA> 0 3.6844597 -3.6844597 24
## 43 <NA> <NA> 5 4.7628879 -4.7628879 24
## 44 <NA> <NA> 3 8.4438118 8.4438118 24
## 45 <NA> <NA> 0 31.0424924 31.0424924 18
## 46 <NA> <NA> 2 21.6102924 21.6102924 26
## 47 <NA> <NA> 6 10.4745755 10.4745755 28
## 48 <NA> <NA> 3 24.5855168 -24.5855168 26
## 49 <NA> <NA> 7 2.5322752 2.5322752 26
## 50 <NA> <NA> 0 26.3807675 -26.3807675 28
## 51 <NA> <NA> 0 28.1855382 28.1855382 28
## 52 <NA> <NA> 0 37.4554773 37.4554773 20
## 53 <NA> <NA> 4 3.9619395 -3.9619395 16
## 54 <NA> <NA> 2 18.3368459 -18.3368459 20
## 55 <NA> <NA> 2 3.4997450 3.4997450 24
## 56 <NA> <NA> 4 21.7294751 -21.7294751 24
## 57 <NA> <NA> 1 19.6454854 19.6454854 28
## 58 <NA> <NA> 0 NA NA 28
## 59 <NA> <NA> 5 3.4715157 3.4715157 28
## 60 <NA> <NA> 5 0.5392246 0.5392246 26
## 61 <NA> <NA> 6 7.5869245 7.5869245 28
## 62 <NA> <NA> 1 7.2886344 -7.2886344 28
## 63 <NA> <NA> 0 6.8275492 6.8275492 28
## 64 <NA> <NA> 3 10.4469946 10.4469946 30
## 65 <NA> <NA> 5 20.3914665 20.3914665 26
## 66 <NA> <NA> 4 6.4051709 6.4051709 12
## 67 <NA> <NA> 2 5.4131884 -5.4131884 16
## 68 <NA> <NA> 8 1.3893721 1.3893721 24
## PloidyLow diPloidyLow sfPloidy disfPloidy annual disfPloidy_corrected
## 1 2 0 2 0 0.00000000 0
## 2 2 0 2 0 0.00000000 0
## 3 NA <NA> 3 1 0.00000000 1
## 4 2 0 2 0 0.00000000 0
## 5 NA <NA> 4 1 0.00000000 0
## 6 2 0 4 1 0.00000000 1
## 7 2 0 4 1 0.00000000 1
## 8 2 0 4 1 0.00000000 1
## 9 2 0 4 1 0.00000000 1
## 10 2 0 4 1 0.00000000 1
## 11 2 0 3 1 0.00000000 1
## 12 2 0 4 1 0.00000000 1
## 13 2 0 4 1 0.00000000 1
## 14 2 0 3 1 0.00000000 1
## 15 2 0 3 1 0.00000000 1
## 16 2 0 3 1 0.00000000 1
## 17 2 0 3 1 0.00000000 1
## 18 2 0 3 1 0.00000000 1
## 19 2 0 3 1 0.00000000 1
## 20 2 0 3 1 0.00000000 1
## 21 4 1 4 1 0.00000000 1
## 22 4 1 4 1 0.00000000 1
## 23 2 0 2 0 0.00000000 0
## 24 NA <NA> 2 0 0.00000000 0
## 25 NA <NA> 2 0 0.00000000 0
## 26 NA <NA> 4 1 0.00000000 1
## 27 NA <NA> 3 1 0.00000000 0
## 28 NA <NA> 3 1 0.00000000 1
## 29 2 0 2 0 1.00000000 0
## 30 NA <NA> 4 1 0.00000000 1
## 31 2 0 3 1 0.00000000 1
## 32 NA <NA> 3 1 0.00000000 1
## 33 NA <NA> 4 1 0.00000000 0
## 34 NA <NA> 4 1 0.00000000 0
## 35 NA <NA> 4 1 0.00000000 0
## 36 NA <NA> 7 1 0.00000000 1
## 37 NA <NA> 4 1 0.00000000 0
## 38 NA <NA> 4 1 0.00000000 0
## 39 NA <NA> 3 1 0.00000000 1
## 40 NA <NA> 3 1 0.00000000 0
## 41 NA <NA> 3 1 0.00000000 0
## 42 NA <NA> 3 1 0.00000000 0
## 43 NA <NA> 3 1 0.00000000 0
## 44 NA <NA> 3 1 0.00000000 1
## 45 NA <NA> 2 0 0.00000000 0
## 46 NA <NA> 2 0 0.00000000 0
## 47 NA <NA> 4 1 0.00000000 1
## 48 NA <NA> 4 1 0.00000000 1
## 49 NA <NA> 4 1 0.00000000 1
## 50 NA <NA> 2 0 0.06306306 0
## 51 NA <NA> 3 1 0.00000000 1
## 52 NA <NA> 2 0 0.00000000 0
## 53 NA <NA> 2 0 0.00000000 0
## 54 NA <NA> 3 1 0.00000000 1
## 55 NA <NA> 3 1 0.00000000 1
## 56 NA <NA> 3 1 0.00000000 1
## 57 NA <NA> 4 1 0.00000000 1
## 58 NA <NA> 4 1 0.02777778 1
## 59 NA <NA> 4 1 0.00000000 1
## 60 NA <NA> 4 1 0.00000000 1
## 61 NA <NA> 4 1 0.00000000 1
## 62 NA <NA> 4 1 0.00000000 1
## 63 NA <NA> 4 1 0.00000000 1
## 64 NA <NA> 4 1 0.00000000 1
## 65 NA <NA> 4 1 0.00000000 1
## 66 NA <NA> 2 0 0.00000000 0
## 67 NA <NA> 2 0 0.00000000 0
## 68 NA <NA> 2 0 0.00000000 0
## NewPloidy
## 1 0
## 2 0
## 3 1
## 4 0
## 5 0
## 6 0
## 7 0
## 8 0
## 9 0
## 10 0
## 11 0
## 12 0
## 13 0
## 14 0
## 15 0
## 16 0
## 17 0
## 18 0
## 19 0
## 20 0
## 21 1
## 22 1
## 23 0
## 24 0
## 25 0
## 26 1
## 27 0
## 28 1
## 29 0
## 30 1
## 31 0
## 32 1
## 33 0
## 34 0
## 35 0
## 36 1
## 37 0
## 38 0
## 39 1
## 40 0
## 41 0
## 42 0
## 43 0
## 44 1
## 45 0
## 46 0
## 47 1
## 48 1
## 49 1
## 50 0
## 51 1
## 52 0
## 53 0
## 54 1
## 55 1
## 56 1
## 57 1
## 58 1
## 59 1
## 60 1
## 61 1
## 62 1
## 63 1
## 64 1
## 65 1
## 66 0
## 67 0
## 68 0# Run pgls and allow lambda to vary
model_sub_non<-gls(log10(Num_Introduced + 1) ~ NewPloidy + AbsLatNative + areaNativeScale + Human_Uses + annual, data=ploidy_data_non, correlation=corPagel(value=0, phy=pruned, fixed=FALSE, form=~"Species"), method = "ML", na.action=na.exclude)
# Inspect model fit
plot(model_sub_non)
qqnorm(resid(model_sub_non))
qqline(resid(model_sub_non)) # This looks pretty ok with the raw data but maybe a bit better with the logged values 
# Test for significance
summary(model_sub_non)## Generalized least squares fit by maximum likelihood
## Model: log10(Num_Introduced + 1) ~ NewPloidy + AbsLatNative + areaNativeScale + Human_Uses + annual
## Data: ploidy_data_non
## AIC BIC logLik
## 78.84103 96.35827 -31.42051
##
## Correlation Structure: corPagel
## Formula: ~"Species"
## Parameter estimate(s):
## lambda
## 0.3159921
##
## Coefficients:
## Value Std.Error t-value p-value
## (Intercept) -0.01916736 0.1595369 -0.120144 0.9048
## NewPloidy1 0.25556737 0.1133062 2.255546 0.0278
## AbsLatNative 0.00744467 0.0044432 1.675504 0.0990
## areaNativeScale 0.11014047 0.0628510 1.752407 0.0848
## Human_Uses 0.16554541 0.0221661 7.468403 0.0000
## annual 0.10171056 0.4160290 0.244479 0.8077
##
## Correlation:
## (Intr) NwPld1 AbsLtN arNtvS Hmn_Us
## NewPloidy1 -0.197
## AbsLatNative -0.535 0.226
## areaNativeScale -0.059 -0.006 0.042
## Human_Uses -0.382 -0.168 0.065 -0.267
## annual -0.036 0.047 -0.157 0.081 0.141
##
## Standardized residuals:
## Min Q1 Med Q3 Max
## -2.3179156 -0.6077655 -0.1104878 0.6257097 2.3953282
##
## Residual standard error: 0.4195285
## Degrees of freedom: 66 total; 60 residualAnova(model_sub_non, type=2, contrasts=list(topic=contr.sum)) # Type 2 anova ## Analysis of Deviance Table (Type II tests)
##
## Response: log10(Num_Introduced + 1)
## Df Chisq Pr(>Chisq)
## NewPloidy 1 5.0875 0.02410 *
## AbsLatNative 1 2.8073 0.09384 .
## areaNativeScale 1 3.0709 0.07970 .
## Human_Uses 1 55.7770 8.117e-14 ***
## annual 1 0.0598 0.80686
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# Not significant but the estimate is in the direction we would expect and is getting close to significance (p = 0.0977)
# Maybe this can be reported as marginally significant?
# Subset the data to symbiotic species
ploidy_data_sym <- ploidy_data1 %>%
filter(Fixer == 1)
ploidy_data_sym## Species Genus areaIntroduced
## 1 Abrus_precatorius Abrus 1.480000e+11
## 2 Acacia_acuminata Acacia 0.000000e+00
## 3 Acacia_alata Acacia 0.000000e+00
## 4 Acacia_ampliceps Acacia 0.000000e+00
## 5 Acacia_aulacocarpa Acacia 0.000000e+00
## 6 Acacia_auriculiformis Acacia 1.120000e+13
## 7 Acacia_baileyana Acacia 1.070000e+13
## 8 Acacia_berlandieri Acacia 0.000000e+00
## 9 Acacia_brachybotrya Acacia 1.150000e+11
## 10 Acacia_caffra Acacia 1.890000e+11
## 11 Acacia_calamifolia Acacia 1.284364e+09
## 12 Acacia_cardiophylla Acacia 2.680000e+11
## 13 Acacia_catechu Acacia 2.290000e+12
## 14 Acacia_caven Acacia 0.000000e+00
## 15 Acacia_cincinnata Acacia 0.000000e+00
## 16 Acacia_colei Acacia 0.000000e+00
## 17 Acacia_confusa Acacia 3.580000e+12
## 18 Acacia_cultriformis Acacia 2.080000e+13
## 19 Acacia_dealbata Acacia 1.450000e+13
## 20 Acacia_deanei Acacia 0.000000e+00
## 21 Acacia_decurrens Acacia 1.000000e+13
## 22 Acacia_elata Acacia 9.680000e+12
## 23 Acacia_elongata Acacia 0.000000e+00
## 24 Acacia_falciformis Acacia 2.680000e+11
## 25 Acacia_galpinii Acacia 0.000000e+00
## 26 Acacia_gerrardii Acacia 0.000000e+00
## 27 Acacia_glaucoptera Acacia 0.000000e+00
## 28 Acacia_hockii Acacia 0.000000e+00
## 29 Acacia_irrorata Acacia 2.680000e+11
## 30 Acacia_karroo Acacia 8.220000e+12
## 31 Acacia_kirkii Acacia 0.000000e+00
## 32 Acacia_koa Acacia 8.508123e+10
## 33 Acacia_leiocalyx Acacia 0.000000e+00
## 34 Acacia_leucoclada Acacia 0.000000e+00
## 35 Acacia_ligulata Acacia 0.000000e+00
## 36 Acacia_longifolia Acacia 2.050000e+13
## 37 Acacia_mearnsii Acacia 1.780000e+13
## 38 Acacia_melanoxylon Acacia 1.710000e+13
## 39 Acacia_modesta Acacia 0.000000e+00
## 40 Acacia_nigrescens Acacia 0.000000e+00
## 41 Acacia_nilotica Acacia 4.860000e+12
## 42 Acacia_notabilis Acacia 1.890000e+11
## 43 Acacia_papyrocarpa Acacia 0.000000e+00
## 44 Acacia_paradoxa Acacia 4.290000e+12
## 45 Acacia_podalyriifolia Acacia 2.260000e+13
## 46 Acacia_polyacantha Acacia 2.581957e+10
## 47 Acacia_pubescens Acacia 0.000000e+00
## 48 Acacia_pulchella Acacia 3.980000e+11
## 49 Acacia_rehmanniana Acacia 0.000000e+00
## 50 Acacia_saligna Acacia 2.030000e+13
## 51 Acacia_senegal Acacia 9.430000e+12
## 52 Acacia_seyal Acacia 3.610000e+12
## 53 Acacia_spectabilis Acacia 2.410000e+12
## 54 Acacia_spinescens Acacia 1.890000e+11
## 55 Acacia_suaveolens Acacia 2.120000e+12
## 56 Acacia_terminalis Acacia 3.190000e+11
## 57 Acacia_tetragonophylla Acacia 0.000000e+00
## 58 Acacia_tortilis Acacia 3.350000e+12
## 59 Acacia_triptera Acacia 0.000000e+00
## 60 Acacia_verticillata Acacia 2.280000e+12
## 61 Acacia_victoriae Acacia 0.000000e+00
## 62 Acacia_xanthophloea Acacia 0.000000e+00
## 63 Acmispon_brachycarpus Acmispon 0.000000e+00
## 64 Acmispon_parviflorus Acmispon 0.000000e+00
## 65 Acmispon_wrangelianus Acmispon 0.000000e+00
## 66 Adenocarpus_complicatus Adenocarpus 0.000000e+00
## 67 Adenocarpus_decorticans Adenocarpus 0.000000e+00
## 68 Adenocarpus_foliolosus Adenocarpus 0.000000e+00
## 69 Aeschynomene_afraspera Aeschynomene 0.000000e+00
## 70 Aeschynomene_americana Aeschynomene 1.320000e+13
## 71 Aeschynomene_ciliata Aeschynomene 0.000000e+00
## 72 Aeschynomene_falcata Aeschynomene 1.140000e+12
## 73 Aeschynomene_indica Aeschynomene 5.746899e+10
## 74 Aeschynomene_pratensis Aeschynomene 0.000000e+00
## 75 Aeschynomene_rudis Aeschynomene 1.700000e+12
## 76 Aeschynomene_scabra <NA> NA
## 77 Aeschynomene_schimperi Aeschynomene 0.000000e+00
## 78 Aeschynomene_sensitiva Aeschynomene 3.779767e+09
## 79 Aeschynomene_virginica Aeschynomene 0.000000e+00
## 80 Albizia_guachapele Albizia 8.080000e+11
## 81 Albizia_julibrissin Albizia 3.040000e+13
## 82 Albizia_kalkora Albizia 0.000000e+00
## 83 Albizia_lebbeck Albizia 4.660000e+13
## 84 Albizia_lebbekoides Albizia 0.000000e+00
## 85 Albizia_procera Albizia 1.640000e+13
## 86 Alhagi_sparsifolia Alhagi 0.000000e+00
## 87 Amicia_zygomeris Amicia 0.000000e+00
## 88 Ammopiptanthus_mongolicus Ammopiptanthus 0.000000e+00
## 89 Amorpha_californica Amorpha 0.000000e+00
## 90 Amorpha_canescens Amorpha 0.000000e+00
## 91 Amorpha_fruticosa Amorpha 2.400000e+13
## 92 Amphicarpaea_bracteata Amphicarpaea 0.000000e+00
## 93 Amphithalea_ericifolia Amphithalea 0.000000e+00
## 94 Amphithalea_intermedia Amphithalea 0.000000e+00
## 95 Anadenanthera_colubrina Anadenanthera 2.055545e+09
## 96 Anadenanthera_peregrina <NA> NA
## 97 Andira_inermis Andira 2.840000e+12
## 98 Anthyllis_cornicina Anthyllis 0.000000e+00
## 99 Anthyllis_lotoides Anthyllis 0.000000e+00
## 100 Anthyllis_montana Anthyllis 0.000000e+00
## 101 Anthyllis_vulneraria <NA> NA
## 102 Antopetitia_abyssinica Antopetitia 0.000000e+00
## 103 Aotus_ericoides Aotus 0.000000e+00
## 104 Apios_americana Apios 1.520000e+12
## 105 Arachis_hypogaea Arachis 6.370000e+13
## 106 Argyrolobium_uniflorum <NA> NA
## 107 Argyrolobium_zanonii Argyrolobium 0.000000e+00
## 108 Aspalathus_cephalotes Aspalathus 0.000000e+00
## 109 Aspalathus_pachyloba Aspalathus 0.000000e+00
## 110 Aspalathus_recurva Aspalathus 0.000000e+00
## 111 Astragalus_adsurgens Astragalus 0.000000e+00
## 112 Astragalus_allochrous Astragalus 0.000000e+00
## 113 Astragalus_americanus Astragalus 0.000000e+00
## 114 Astragalus_atropilosulus Astragalus 0.000000e+00
## 115 Astragalus_boeticus Astragalus 0.000000e+00
## 116 Astragalus_canadensis Astragalus 0.000000e+00
## 117 Astragalus_cicer Astragalus 2.750000e+12
## 118 Astragalus_corrugatus Astragalus 0.000000e+00
## 119 Astragalus_epiglottis Astragalus 0.000000e+00
## 120 Astragalus_eucosmus Astragalus 0.000000e+00
## 121 Astragalus_frigidus Astragalus 0.000000e+00
## 122 Astragalus_miser Astragalus 0.000000e+00
## 123 Astragalus_mollissimus Astragalus 0.000000e+00
## 124 Astragalus_neglectus Astragalus 0.000000e+00
## 125 Astragalus_nothoxys Astragalus 0.000000e+00
## 126 Astragalus_odoratus Astragalus 2.310000e+11
## 127 Astragalus_pehuenches Astragalus 0.000000e+00
## 128 Astragalus_scaberrimus Astragalus 0.000000e+00
## 129 Astragalus_sinicus Astragalus 0.000000e+00
## 130 Astragalus_spatulatus Astragalus 0.000000e+00
## 131 Astragalus_stevenianus Astragalus 0.000000e+00
## 132 Astragalus_tenellus Astragalus 0.000000e+00
## 133 Astragalus_tribuloides Astragalus 0.000000e+00
## 134 Astragalus_uliginosus Astragalus 0.000000e+00
## 135 Astragalus_umbellatus Astragalus 0.000000e+00
## 136 Baphia_massaiensis Baphia 0.000000e+00
## 137 Baptisia_alba Baptisia 0.000000e+00
## 138 Baptisia_australis Baptisia 1.360000e+13
## 139 Baptisia_bracteata Baptisia 0.000000e+00
## 140 Baptisia_tinctoria Baptisia 0.000000e+00
## 141 Bauhinia_vahlii Bauhinia 2.400000e+12
## 142 Bituminaria_bituminosa Bituminaria 1.320000e+11
## 143 Bobgunnia_madagascariensis Bobgunnia 1.470000e+11
## 144 Bolusanthus_speciosus Bolusanthus 3.680000e+12
## 145 Bossiaea_linophylla Bossiaea 0.000000e+00
## 146 Bowdichia_virgilioides Bowdichia 0.000000e+00
## 147 Brya_ebenus Brya 4.300000e+11
## 148 Cadia_purpurea Cadia 0.000000e+00
## 149 Cajanus_cajan Cajanus 4.600000e+13
## 150 Cajanus_lineatus Cajanus 0.000000e+00
## 151 Calliandra_eriophylla Calliandra 0.000000e+00
## 152 Calliandra_houstoniana Calliandra 2.180000e+12
## 153 Calpurnia_aurea Calpurnia 2.190000e+12
## 154 Camptosema_rubicundum Camptosema 7.460000e+11
## 155 Campylotropis_macrocarpa Campylotropis 0.000000e+00
## 156 Canavalia_brasiliensis Canavalia 1.470000e+11
## 157 Canavalia_cathartica Canavalia 1.685873e+10
## 158 Canavalia_gladiata Canavalia 2.740000e+13
## 159 Canavalia_rosea Canavalia 2.527217e+08
## 160 Caragana_erinacea Caragana 0.000000e+00
## 161 Caragana_korshinskii Caragana 0.000000e+00
## 162 Caragana_microphylla Caragana 1.320000e+12
## 163 Carmichaelia_arborea Carmichaelia 0.000000e+00
## 164 Carmichaelia_kirkii Carmichaelia 0.000000e+00
## 165 Centrolobium_paraense <NA> NA
## 166 Centrolobium_tomentosum Centrolobium 0.000000e+00
## 167 Centrosema_pubescens Centrosema 2.510000e+13
## 168 Centrosema_virginianum Centrosema 5.540000e+11
## 169 Chadsia_grevei Chadsia 0.000000e+00
## 170 Chamaecrista_fasciculata Chamaecrista 2.055545e+09
## 171 Chamaecrista_nictitans Chamaecrista 2.160000e+12
## 172 Chorizema_cordatum Chorizema 0.000000e+00
## 173 Cicer_arietinum Cicer 7.410000e+13
## 174 Cicer_echinospermum Cicer 0.000000e+00
## 175 Cicer_pinnatifidum Cicer 0.000000e+00
## 176 Cicer_reticulatum Cicer 0.000000e+00
## 177 Clianthus_puniceus Clianthus 3.610000e+11
## 178 Colutea_arborescens Colutea 1.170000e+13
## 179 Coronilla_coronata Coronilla 0.000000e+00
## 180 Coronilla_juncea Coronilla 0.000000e+00
## 181 Coronilla_minima Coronilla 0.000000e+00
## 182 Coronilla_repanda Coronilla 0.000000e+00
## 183 Coronilla_scorpioides Coronilla 7.940000e+12
## 184 Coronilla_vaginalis Coronilla 0.000000e+00
## 185 Crotalaria_assamica Crotalaria 0.000000e+00
## 186 Crotalaria_atrorubens Crotalaria 0.000000e+00
## 187 Crotalaria_calycina Crotalaria 0.000000e+00
## 188 Crotalaria_capensis Crotalaria 8.480000e+11
## 189 Crotalaria_comosa Crotalaria 0.000000e+00
## 190 Crotalaria_glaucoides Crotalaria 0.000000e+00
## 191 Crotalaria_goreensis Crotalaria 2.100000e+13
## 192 Crotalaria_incana Crotalaria 1.430000e+13
## 193 Crotalaria_lanceolata Crotalaria 2.080000e+12
## 194 Crotalaria_ochroleuca Crotalaria 1.260000e+13
## 195 Crotalaria_pallida Crotalaria 1.730000e+13
## 196 Crotalaria_podocarpa Crotalaria 0.000000e+00
## 197 Crotalaria_senegalensis Crotalaria 3.420000e+11
## 198 Crotalaria_sphaerocarpa Crotalaria 0.000000e+00
## 199 Crotalaria_trichotoma Crotalaria 9.410000e+12
## 200 Cyamopsis_serrata Cyamopsis 0.000000e+00
## 201 Cyamopsis_tetragonoloba Cyamopsis 1.580000e+13
## 202 Cyclopia_genistoides <NA> NA
## 203 Cyclopia_maculata Cyclopia 0.000000e+00
## 204 Cyclopia_meyeriana <NA> NA
## 205 Cyclopia_pubescens <NA> NA
## 206 Cytisus_arboreus Cytisus 0.000000e+00
## 207 Cytisus_multiflorus <NA> NA
## 208 Cytisus_scoparius <NA> NA
## 209 Cytisus_striatus <NA> NA
## 210 Cytisus_villosus Cytisus 0.000000e+00
## 211 Dalbergia_assamica Dalbergia 5.820000e+11
## 212 Dalbergia_frutescens Dalbergia 0.000000e+00
## 213 Dalbergia_melanoxylon Dalbergia 1.060000e+12
## 214 Dalbergia_miscolobium Dalbergia 0.000000e+00
## 215 Dalbergia_monetaria Dalbergia 0.000000e+00
## 216 Dalbergia_nigra Dalbergia 0.000000e+00
## 217 Dalbergia_sissoo Dalbergia 1.660000e+13
## 218 Dalea_candida Dalea 0.000000e+00
## 219 Dalea_leporina Dalea 0.000000e+00
## 220 Dalea_mollissima Dalea 0.000000e+00
## 221 Dalea_pogonathera Dalea 0.000000e+00
## 222 Dalea_purpurea Dalea 0.000000e+00
## 223 Daviesia_acicularis Daviesia 0.000000e+00
## 224 Daviesia_corymbosa Daviesia 0.000000e+00
## 225 Daviesia_genistifolia Daviesia 0.000000e+00
## 226 Daviesia_leptophylla Daviesia 0.000000e+00
## 227 Daviesia_ulicifolia Daviesia 0.000000e+00
## 228 Derris_elliptica Derris 3.240000e+12
## 229 Desmanthus_illinoensis Desmanthus 3.827134e+10
## 230 Desmanthus_virgatus Desmanthus 1.420000e+13
## 231 Desmodium_barbatum Desmodium 0.000000e+00
## 232 Desmodium_cuspidatum Desmodium 0.000000e+00
## 233 Desmodium_elegans Desmodium 2.310000e+11
## 234 Desmodium_gangeticum Desmodium 2.387763e+10
## 235 Desmodium_glutinosum Desmodium 0.000000e+00
## 236 Desmodium_heterocarpon Desmodium 1.520000e+12
## 237 Desmodium_microphyllum Desmodium 0.000000e+00
## 238 Desmodium_scorpiurus Desmodium 9.580000e+12
## 239 Desmodium_tortuosum Desmodium 2.920000e+13
## 240 Desmodium_uncinatum Desmodium 7.270000e+12
## 241 Dichilus_lebeckioides Dichilus 0.000000e+00
## 242 Dichilus_strictus Dichilus 0.000000e+00
## 243 Dioclea_virgata Dioclea 2.550000e+12
## 244 Diphysa_americana Diphysa 6.080000e+11
## 245 Dipogon_lignosus Dipogon 1.950000e+13
## 246 Dolichos_trilobus Dolichos 0.000000e+00
## 247 Dorycnium_pentaphyllum Dorycnium 2.680000e+11
## 248 Dorycnium_rectum Dorycnium 0.000000e+00
## 249 Dumasia_villosa Dumasia 0.000000e+00
## 250 Ebenus_pinnata Ebenus 0.000000e+00
## 251 Entada_abyssinica Entada 0.000000e+00
## 252 Enterolobium_contortisiliquum Enterolobium 9.720000e+11
## 253 Enterolobium_cyclocarpum Enterolobium 4.290000e+12
## 254 Erythrina_costaricensis Erythrina 0.000000e+00
## 255 Erythrina_fusca Erythrina 4.530000e+12
## 256 Erythrina_lysistemon Erythrina 6.530000e+12
## 257 Erythrina_speciosa Erythrina 3.600000e+12
## 258 Euchresta_japonica Euchresta 0.000000e+00
## 259 Faidherbia_albida Faidherbia 9.970000e+11
## 260 Flemingia_macrophylla Flemingia 7.600000e+12
## 261 Galactia_striata Galactia 6.139767e+08
## 262 Galega_officinalis Galega 1.720000e+13
## 263 Galega_orientalis Galega 8.740000e+12
## 264 Gastrolobium_bilobum Gastrolobium 0.000000e+00
## 265 Gastrolobium_parviflorum Gastrolobium 0.000000e+00
## 266 Genista_anglica Genista 0.000000e+00
## 267 Genista_canariensis Genista 8.470000e+12
## 268 Genista_cinerea Genista 0.000000e+00
## 269 Genista_falcata Genista 0.000000e+00
## 270 Genista_florida Genista 0.000000e+00
## 271 Genista_germanica Genista 1.110000e+11
## 272 Genista_linifolia Genista 5.090000e+12
## 273 Genista_monspessulana Genista 1.660000e+13
## 274 Genista_radiata Genista 0.000000e+00
## 275 Genista_tenera Genista 0.000000e+00
## 276 Gliricidia_sepium Gliricidia 1.920000e+13
## 277 Glycine_canescens Glycine 0.000000e+00
## 278 Glycine_clandestina Glycine 0.000000e+00
## 279 Glycine_max Glycine 8.870000e+13
## 280 Glycine_microphylla Glycine 0.000000e+00
## 281 Glycine_tabacina Glycine 5.820000e+11
## 282 Glycyrrhiza_glabra Glycyrrhiza 1.540000e+13
## 283 Glycyrrhiza_lepidota Glycyrrhiza 0.000000e+00
## 284 Glycyrrhiza_pallidiflora Glycyrrhiza 0.000000e+00
## 285 Glycyrrhiza_uralensis Glycyrrhiza 0.000000e+00
## 286 Gompholobium_minus Gompholobium 0.000000e+00
## 287 Goodia_lotifolia Goodia 1.150000e+11
## 288 Gueldenstaedtia_verna Gueldenstaedtia 0.000000e+00
## 289 Halimodendron_halodendron Halimodendron 7.170000e+12
## 290 Hardenbergia_comptoniana Hardenbergia 1.320000e+11
## 291 Hardenbergia_violacea Hardenbergia 2.055545e+09
## 292 Havardia_pallens Havardia 0.000000e+00
## 293 Hebestigma_cubense Hebestigma 0.000000e+00
## 294 Hedysarum_alpinum Hedysarum 0.000000e+00
## 295 Hedysarum_boreale Hedysarum 0.000000e+00
## 296 Hedysarum_caucasicum Hedysarum 0.000000e+00
## 297 Hedysarum_coronarium Hedysarum 6.850000e+12
## 298 Hedysarum_vicioides Hedysarum 0.000000e+00
## 299 Hesperolaburnum_platycarpum Hesperolaburnum 0.000000e+00
## 300 Hippocrepis_emerus Hippocrepis 7.170000e+11
## 301 Hippocrepis_unisiliquosa Hippocrepis 0.000000e+00
## 302 Hoita_macrostachya Hoita 0.000000e+00
## 303 Hovea_elliptica Hovea 1.150000e+11
## 304 Hovea_trisperma Hovea 0.000000e+00
## 305 Hypocalyptus_coluteoides Hypocalyptus 0.000000e+00
## 306 Hypocalyptus_sophoroides Hypocalyptus 0.000000e+00
## 307 Indigastrum_argyroides Indigastrum 0.000000e+00
## 308 Indigofera_alternans Indigofera 0.000000e+00
## 309 Indigofera_argentea Indigofera 0.000000e+00
## 310 Indigofera_arrecta <NA> NA
## 311 Indigofera_astragalina Indigofera 3.556257e+08
## 312 Indigofera_australis Indigofera 2.670000e+12
## 313 Indigofera_cordifolia Indigofera 0.000000e+00
## 314 Indigofera_decora Indigofera 2.740000e+12
## 315 Indigofera_demissa Indigofera 0.000000e+00
## 316 Indigofera_emarginella Indigofera 0.000000e+00
## 317 Indigofera_filifolia <NA> NA
## 318 Indigofera_hedyantha Indigofera 0.000000e+00
## 319 Indigofera_hirsuta Indigofera 2.150000e+12
## 320 Indigofera_kirilowii Indigofera 8.170000e+12
## 321 Indigofera_linifolia Indigofera 2.645045e+09
## 322 Indigofera_lupatana Indigofera 0.000000e+00
## 323 Indigofera_microcarpa Indigofera 0.000000e+00
## 324 Indigofera_nummulariifolia Indigofera 0.000000e+00
## 325 Indigofera_oblongifolia Indigofera 0.000000e+00
## 326 Indigofera_praticola Indigofera 0.000000e+00
## 327 Indigofera_pseudotinctoria Indigofera 0.000000e+00
## 328 Indigofera_pulchra Indigofera 0.000000e+00
## 329 Indigofera_rhynchocarpa Indigofera 0.000000e+00
## 330 Indigofera_schimperi Indigofera 0.000000e+00
## 331 Indigofera_sessiliflora Indigofera 0.000000e+00
## 332 Indigofera_spicata Indigofera 1.280000e+11
## 333 Indigofera_strobilifera Indigofera 0.000000e+00
## 334 Indigofera_suffruticosa Indigofera 5.580000e+12
## 335 Indigofera_swaziensis Indigofera 0.000000e+00
## 336 Indigofera_tinctoria Indigofera 3.140000e+12
## 337 Inga_densiflora Inga 0.000000e+00
## 338 Inga_edulis Inga 6.600000e+12
## 339 Inga_heterophylla Inga 0.000000e+00
## 340 Inga_laurina Inga 2.120000e+12
## 341 Inga_leiocalycina Inga 0.000000e+00
## 342 Inga_oerstediana Inga 0.000000e+00
## 343 Inga_punctata Inga 0.000000e+00
## 344 Inga_sertulifera Inga 0.000000e+00
## 345 Inga_spectabilis Inga 0.000000e+00
## 346 Inga_umbellifera Inga 0.000000e+00
## 347 Inga_vera Inga 2.120000e+12
## 348 Inocarpus_fagifer Inocarpus 4.700590e+09
## 349 Isotropis_cuneifolia Isotropis 0.000000e+00
## 350 Jacksonia_horrida Jacksonia 0.000000e+00
## 351 Kennedia_beckxiana Kennedia 0.000000e+00
## 352 Kennedia_coccinea Kennedia 0.000000e+00
## 353 Kennedia_nigricans Kennedia 0.000000e+00
## 354 Kennedia_prostrata Kennedia 0.000000e+00
## 355 Kennedia_rubicunda Kennedia 4.340000e+11
## 356 Kummerowia_stipulacea Kummerowia 2.800000e+12
## 357 Kummerowia_striata Kummerowia 2.530000e+12
## 358 Lablab_purpureus Lablab 3.350000e+13
## 359 Laburnum_anagyroides Laburnum 2.410000e+13
## 360 Lamprolobium_fruticosum Lamprolobium 1.300000e+11
## 361 Lathyrus_aphaca Lathyrus 1.120000e+13
## 362 Lathyrus_cicera Lathyrus 6.060000e+11
## 363 Lathyrus_clymenum Lathyrus 8.970000e+11
## 364 Lathyrus_hirsutus Lathyrus 4.970000e+12
## 365 Lathyrus_japonicus Lathyrus 0.000000e+00
## 366 Lathyrus_littoralis Lathyrus 0.000000e+00
## 367 Lathyrus_nevadensis Lathyrus 0.000000e+00
## 368 Lathyrus_niger Lathyrus 3.460000e+11
## 369 Lathyrus_nissolia Lathyrus 8.380000e+12
## 370 Lathyrus_ochrus Lathyrus 1.170000e+11
## 371 Lathyrus_odoratus Lathyrus 6.380000e+13
## 372 Lathyrus_palustris Lathyrus 0.000000e+00
## 373 Lathyrus_pratensis <NA> NA
## 374 Lathyrus_sativus Lathyrus 5.410000e+13
## 375 Lathyrus_sphaericus Lathyrus 8.420000e+12
## 376 Lathyrus_tingitanus Lathyrus 7.130000e+12
## 377 Lebeckia_cytisoides Lebeckia 0.000000e+00
## 378 Lens_culinaris Lens 2.780000e+13
## 379 Lens_ervoides Lens 0.000000e+00
## 380 Lespedeza_angustifolia Lespedeza 0.000000e+00
## 381 Lespedeza_bicolor Lespedeza 8.250000e+12
## 382 Lespedeza_capitata Lespedeza 0.000000e+00
## 383 Lespedeza_cyrtobotrya Lespedeza 8.170000e+12
## 384 Lespedeza_davidii Lespedeza 0.000000e+00
## 385 Lespedeza_floribunda Lespedeza 0.000000e+00
## 386 Lespedeza_hirta Lespedeza 0.000000e+00
## 387 Lespedeza_japonica Lespedeza 8.540000e+12
## 388 Lespedeza_juncea Lespedeza 1.090000e+13
## 389 Lespedeza_maximowiczii Lespedeza 0.000000e+00
## 390 Lespedeza_procumbens Lespedeza 0.000000e+00
## 391 Lespedeza_repens Lespedeza 0.000000e+00
## 392 Lespedeza_stuevei Lespedeza 0.000000e+00
## 393 Lespedeza_thunbergii Lespedeza 6.120000e+11
## 394 Lespedeza_tomentosa Lespedeza 0.000000e+00
## 395 Lespedeza_virgata Lespedeza 2.750000e+11
## 396 Lespedeza_virginica Lespedeza 0.000000e+00
## 397 Lessertia_herbacea <NA> NA
## 398 Leucaena_diversifolia Leucaena 2.490000e+12
## 399 Leucaena_greggii Leucaena 2.940000e+11
## 400 Leucaena_involucrata Leucaena 0.000000e+00
## 401 Leucaena_leucocephala <NA> NA
## 402 Leucaena_multicapitula Leucaena 0.000000e+00
## 403 Leucaena_pulverulenta Leucaena 5.470000e+12
## 404 Leucaena_retusa Leucaena 1.120000e+11
## 405 Leucaena_salvadorensis Leucaena 0.000000e+00
## 406 Leucaena_shannonii Leucaena 0.000000e+00
## 407 Leucaena_trichodes Leucaena 0.000000e+00
## 408 Liparia_splendens Liparia 0.000000e+00
## 409 Lonchocarpus_eriocarinalis Lonchocarpus 0.000000e+00
## 410 Lotononis_platycarpa Lotononis 0.000000e+00
## 411 Lotononis_rabenaviana Lotononis 0.000000e+00
## 412 Lotus_angustissimus Lotus 1.100000e+13
## 413 Lotus_arabicus Lotus 0.000000e+00
## 414 Lotus_arenarius Lotus 0.000000e+00
## 415 Lotus_australis Lotus 0.000000e+00
## 416 Lotus_conimbricensis Lotus 0.000000e+00
## 417 Lotus_corniculatus <NA> NA
## 418 Lotus_cruentus Lotus 0.000000e+00
## 419 Lotus_cytisoides Lotus 0.000000e+00
## 420 Lotus_edulis Lotus 0.000000e+00
## 421 Lotus_halophilus Lotus 0.000000e+00
## 422 Lotus_longesiliquosus Lotus 0.000000e+00
## 423 Lotus_maroccanus Lotus 0.000000e+00
## 424 Lotus_ornithopodioides Lotus 7.940000e+12
## 425 Lotus_parviflorus Lotus 0.000000e+00
## 426 Lotus_pedunculatus <NA> NA
## 427 Lotus_peregrinus Lotus 0.000000e+00
## 428 Lotus_schoelleri Lotus 0.000000e+00
## 429 Lotus_subbiflorus Lotus 0.000000e+00
## 430 Lotus_tenuis Lotus 8.460000e+11
## 431 Lotus_weilleri Lotus 0.000000e+00
## 432 Lupinus_albifrons Lupinus 0.000000e+00
## 433 Lupinus_albus Lupinus 3.770000e+13
## 434 Lupinus_angustifolius Lupinus 3.150000e+13
## 435 Lupinus_arboreus Lupinus 5.590000e+12
## 436 Lupinus_arcticus Lupinus 0.000000e+00
## 437 Lupinus_argenteus Lupinus 0.000000e+00
## 438 Lupinus_atlanticus Lupinus 0.000000e+00
## 439 Lupinus_cosentinii Lupinus 1.280000e+13
## 440 Lupinus_digitatus Lupinus 0.000000e+00
## 441 Lupinus_hispanicus Lupinus 0.000000e+00
## 442 Lupinus_latifolius Lupinus 0.000000e+00
## 443 Lupinus_lepidus Lupinus 0.000000e+00
## 444 Lupinus_luteus Lupinus 3.320000e+13
## 445 Lupinus_mexicanus Lupinus 4.560000e+11
## 446 Lupinus_mutabilis Lupinus 7.120000e+12
## 447 Lupinus_nanus Lupinus 0.000000e+00
## 448 Lupinus_nootkatensis Lupinus 7.270000e+11
## 449 Lupinus_palaestinus Lupinus 0.000000e+00
## 450 Lupinus_perennis Lupinus 1.190000e+13
## 451 Lupinus_pilosus Lupinus 1.130000e+13
## 452 Lupinus_polyphyllus Lupinus 3.010000e+13
## 453 Lupinus_princei Lupinus 0.000000e+00
## 454 Lupinus_pusillus Lupinus 0.000000e+00
## 455 Lupinus_sericeus Lupinus 0.000000e+00
## 456 Lupinus_succulentus Lupinus 0.000000e+00
## 457 Lysiloma_divaricatum Lysiloma 0.000000e+00
## 458 Maackia_amurensis Maackia 1.450000e+13
## 459 Machaerium_aculeatum Machaerium 0.000000e+00
## 460 Machaerium_brasiliense Machaerium 0.000000e+00
## 461 Machaerium_stipitatum Machaerium 0.000000e+00
## 462 Machaerium_villosum Machaerium 0.000000e+00
## 463 Macroptilium_atropurpureum Macroptilium 1.280000e+13
## 464 Macroptilium_gracile Macroptilium 0.000000e+00
## 465 Macroptilium_lathyroides Macroptilium 2.040000e+13
## 466 Macrotyloma_uniflorum Macrotyloma 2.270000e+12
## 467 Medicago_arabica Medicago 2.200000e+13
## 468 Medicago_arborea Medicago 1.590000e+13
## 469 Medicago_brachycarpa Medicago 0.000000e+00
## 470 Medicago_cancellata Medicago 0.000000e+00
## 471 Medicago_carstiensis Medicago 0.000000e+00
## 472 Medicago_constricta Medicago 0.000000e+00
## 473 Medicago_heyniana Medicago 0.000000e+00
## 474 Medicago_hybrida Medicago 0.000000e+00
## 475 Medicago_hypogaea Medicago 0.000000e+00
## 476 Medicago_intertexta <NA> NA
## 477 Medicago_laciniata Medicago 5.390000e+12
## 478 Medicago_lupulina <NA> NA
## 479 Medicago_marina Medicago 0.000000e+00
## 480 Medicago_medicaginoides Medicago 0.000000e+00
## 481 Medicago_monantha Medicago 5.820000e+11
## 482 Medicago_monspeliaca Medicago 1.640000e+13
## 483 Medicago_murex Medicago 0.000000e+00
## 484 Medicago_noeana Medicago 0.000000e+00
## 485 Medicago_orbicularis Medicago 1.450000e+13
## 486 Medicago_papillosa Medicago 0.000000e+00
## 487 Medicago_polyceratia Medicago 0.000000e+00
## 488 Medicago_polymorpha Medicago 4.380000e+13
## 489 Medicago_praecox Medicago 9.780000e+12
## 490 Medicago_radiata Medicago 7.900000e+11
## 491 Medicago_ruthenica Medicago 0.000000e+00
## 492 Medicago_sativa <NA> NA
## 493 Medicago_scutellata Medicago 7.520000e+12
## 494 Medicago_secundiflora Medicago 0.000000e+00
## 495 Medicago_soleirolii Medicago 5.390000e+11
## 496 Medicago_suffruticosa Medicago 0.000000e+00
## 497 Medicago_truncatula Medicago 7.620000e+12
## 498 Medicago_turbinata Medicago 0.000000e+00
## 499 Melilotus_albus Melilotus 3.620000e+13
## 500 Melilotus_indicus Melilotus 4.920000e+13
## 501 Melilotus_officinalis <NA> NA
## 502 Melilotus_sulcatus Melilotus 1.640000e+13
## 503 Melolobium_obcordatum Melolobium 0.000000e+00
## 504 Microlobius_foetidus Microlobius 0.000000e+00
## 505 Millettia_thonningii Millettia 4.380000e+12
## 506 Mimosa_aculeaticarpa Mimosa 0.000000e+00
## 507 Mimosa_albida Mimosa 4.700590e+09
## 508 Mimosa_debilis Mimosa 0.000000e+00
## 509 Mimosa_hirsutissima Mimosa 0.000000e+00
## 510 Mimosa_pigra Mimosa 7.260000e+12
## 511 Mimosa_polycarpa Mimosa 0.000000e+00
## 512 Mimosa_pudica Mimosa 3.070000e+13
## 513 Mimosa_quadrivalvis Mimosa 1.290000e+12
## 514 Mimosa_somnians Mimosa 0.000000e+00
## 515 Mimosa_strigillosa <NA> NA
## 516 Mimosa_tenuiflora Mimosa 0.000000e+00
## 517 Mimozyganthus_carinatus Mimozyganthus 0.000000e+00
## 518 Mirbelia_pungens Mirbelia 0.000000e+00
## 519 Mucuna_nigricans Mucuna 0.000000e+00
## 520 Mundulea_sericea Mundulea 2.120000e+12
## 521 Neorautanenia_mitis Neorautanenia 0.000000e+00
## 522 Neptunia_monosperma Neptunia 0.000000e+00
## 523 Neptunia_oleracea Neptunia 2.055545e+09
## 524 Neptunia_plena Neptunia 4.450000e+12
## 525 Neptunia_pubescens Neptunia 0.000000e+00
## 526 Olneya_tesota Olneya 0.000000e+00
## 527 Onobrychis_arenaria Onobrychis 0.000000e+00
## 528 Onobrychis_cyri Onobrychis 0.000000e+00
## 529 Onobrychis_transcaucasica Onobrychis 0.000000e+00
## 530 Onobrychis_viciifolia <NA> NA
## 531 Ononis_mitissima Ononis 0.000000e+00
## 532 Ononis_natrix Ononis 9.370000e+12
## 533 Ononis_rotundifolia Ononis 0.000000e+00
## 534 Ononis_serrata Ononis 5.390000e+11
## 535 Ononis_vaginalis Ononis 0.000000e+00
## 536 Ophrestia_radicosa Ophrestia 0.000000e+00
## 537 Ormocarpum_trichocarpum Ormocarpum 0.000000e+00
## 538 Ormosia_henryi Ormosia 0.000000e+00
## 539 Ormosia_krugii Ormosia 0.000000e+00
## 540 Ormosia_semicastrata Ormosia 0.000000e+00
## 541 Ornithopus_compressus Ornithopus 1.830000e+13
## 542 Ornithopus_perpusillus <NA> NA
## 543 Ornithopus_pinnatus Ornithopus 1.110000e+13
## 544 Ornithopus_sativus <NA> NA
## 545 Ottleya_strigosa Ottleya 0.000000e+00
## 546 Oxylobium_ellipticum Oxylobium 0.000000e+00
## 547 Oxylobium_robustum Oxylobium 0.000000e+00
## 548 Oxyrhynchus_volubilis Oxyrhynchus 0.000000e+00
## 549 Oxytropis_arctica Oxytropis 0.000000e+00
## 550 Oxytropis_deflexa Oxytropis 0.000000e+00
## 551 Oxytropis_lambertii Oxytropis 0.000000e+00
## 552 Oxytropis_maydelliana Oxytropis 0.000000e+00
## 553 Oxytropis_pilosa Oxytropis 0.000000e+00
## 554 Oxytropis_sericea Oxytropis 0.000000e+00
## 555 Oxytropis_splendens Oxytropis 0.000000e+00
## 556 Pachyrhizus_erosus Pachyrhizus 2.910000e+13
## 557 Parapiptadenia_pterosperma <NA> NA
## 558 Parapiptadenia_rigida Parapiptadenia 2.670000e+12
## 559 Paraserianthes_lophantha Paraserianthes 1.340000e+13
## 560 Parochetus_communis Parochetus 2.680000e+11
## 561 Peltophorum_africanum Peltophorum 4.900000e+12
## 562 Petteria_ramentacea Petteria 0.000000e+00
## 563 Phaseolus_acutifolius Phaseolus 1.070000e+13
## 564 Phaseolus_coccineus Phaseolus 3.740000e+13
## 565 Phaseolus_filiformis Phaseolus 0.000000e+00
## 566 Phaseolus_lunatus Phaseolus 4.080000e+13
## 567 Phaseolus_maculatus Phaseolus 0.000000e+00
## 568 Phaseolus_polystachios Phaseolus 0.000000e+00
## 569 Phaseolus_vulgaris Phaseolus 4.890000e+13
## 570 Phyllodium_pulchellum Phyllodium 4.700590e+09
## 571 Phyllota_phylicoides Phyllota 0.000000e+00
## 572 Piptadenia_flava <NA> NA
## 573 Piptadenia_gonoacantha <NA> NA
## 574 Piptadenia_obliqua Piptadenia 0.000000e+00
## 575 Piptadenia_stipulacea Piptadenia 0.000000e+00
## 576 Piptanthus_nepalensis Piptanthus 2.310000e+11
## 577 Piscidia_piscipula Piscidia 2.770000e+12
## 578 Pisum_sativum Pisum 7.900000e+13
## 579 Pithecellobium_dulce Pithecellobium 2.580000e+13
## 580 Platylobium_formosum Platylobium 0.000000e+00
## 581 Platylobium_obtusangulum Platylobium 0.000000e+00
## 582 Platymiscium_pinnatum Platymiscium 6.628851e+10
## 583 Podalyria_calyptrata <NA> NA
## 584 Podalyria_sericea Podalyria 1.170000e+11
## 585 Podolobium_ilicifolium Podolobium 0.000000e+00
## 586 Poiretia_punctata Poiretia 0.000000e+00
## 587 Prosopis_africana Prosopis 0.000000e+00
## 588 Prosopis_cineraria Prosopis 2.250000e+12
## 589 Prosopis_glandulosa Prosopis 2.340000e+13
## 590 Prosopis_juliflora <NA> NA
## 591 Prosopis_laevigata Prosopis 0.000000e+00
## 592 Prosopis_nigra Prosopis 0.000000e+00
## 593 Prosopis_pallida Prosopis 1.080000e+13
## 594 Prosopis_tamarugo Prosopis 0.000000e+00
## 595 Prosopis_velutina Prosopis 3.470000e+12
## 596 Pseudeminia_comosa Pseudeminia 0.000000e+00
## 597 Pseudovigna_argentea Pseudovigna 3.920000e+11
## 598 Psophocarpus_scandens Psophocarpus 3.370000e+12
## 599 Psophocarpus_tetragonolobus Psophocarpus 2.660000e+13
## 600 Pterocarpus_indicus Pterocarpus 5.360000e+12
## 601 Pterocarpus_macrocarpus Pterocarpus 8.040000e+12
## 602 Pterocarpus_officinalis <NA> NA
## 603 Pueraria_montana Pueraria 4.680000e+12
## 604 Pueraria_phaseoloides Pueraria 1.670000e+13
## 605 Pultenaea_blakelyi Pultenaea 0.000000e+00
## 606 Pultenaea_daphnoides Pultenaea 1.150000e+11
## 607 Pultenaea_densifolia Pultenaea 0.000000e+00
## 608 Pultenaea_flexilis Pultenaea 0.000000e+00
## 609 Pultenaea_myrtoides Pultenaea 0.000000e+00
## 610 Pultenaea_scabra Pultenaea 0.000000e+00
## 611 Pultenaea_stipularis Pultenaea 0.000000e+00
## 612 Pultenaea_tenuifolia Pultenaea 0.000000e+00
## 613 Pultenaea_verruculosa Pultenaea 0.000000e+00
## 614 Retama_monosperma Retama 1.080000e+13
## 615 Retama_raetam Retama 1.440000e+12
## 616 Retama_sphaerocarpa Retama 2.890000e+12
## 617 Rhynchosia_minima Rhynchosia 1.685873e+10
## 618 Robinia_hispida Robinia 6.750000e+12
## 619 Robinia_pseudoacacia Robinia 3.760000e+13
## 620 Robinia_viscosa Robinia 7.890000e+12
## 621 Scorpiurus_muricatus Scorpiurus 2.680000e+11
## 622 Securigera_securidaca Securigera 9.750000e+12
## 623 Securigera_varia Securigera 2.990000e+13
## 624 Sesbania_cannabina Sesbania 6.670000e+12
## 625 Sesbania_drummondii Sesbania 0.000000e+00
## 626 Sesbania_grandiflora Sesbania 1.750000e+13
## 627 Sesbania_herbacea Sesbania 0.000000e+00
## 628 Sesbania_punicea Sesbania 5.330000e+12
## 629 Sesbania_sesban Sesbania 9.750000e+12
## 630 Sesbania_tetraptera Sesbania 0.000000e+00
## 631 Sesbania_tomentosa Sesbania 0.000000e+00
## 632 Shuteria_involucrata Shuteria 1.060000e+12
## 633 Sophora_arizonica Sophora 0.000000e+00
## 634 Sophora_chrysophylla Sophora 0.000000e+00
## 635 Sophora_davidii Sophora 3.250000e+12
## 636 Sophora_flavescens Sophora 2.310000e+11
## 637 Sophora_microphylla Sophora 8.690000e+12
## 638 Sophora_prostrata Sophora 2.310000e+11
## 639 Sophora_secundiflora Sophora 2.020000e+12
## 640 Sophora_tetraptera Sophora 0.000000e+00
## 641 Sophora_tomentosa Sophora 3.580000e+12
## 642 Spartium_junceum <NA> NA
## 643 Strongylodon_macrobotrys Strongylodon 2.290000e+11
## 644 Strophostyles_umbellata Strophostyles 0.000000e+00
## 645 Stryphnodendron_adstringens Stryphnodendron 0.000000e+00
## 646 Stylosanthes_angustifolia Stylosanthes 0.000000e+00
## 647 Stylosanthes_biflora Stylosanthes 0.000000e+00
## 648 Stylosanthes_erecta Stylosanthes 0.000000e+00
## 649 Stylosanthes_fruticosa Stylosanthes 0.000000e+00
## 650 Stylosanthes_guianensis Stylosanthes 1.910000e+13
## 651 Stylosanthes_hamata Stylosanthes 2.750000e+11
## 652 Stylosanthes_humilis Stylosanthes 1.260000e+13
## 653 Stylosanthes_macrocephala Stylosanthes 0.000000e+00
## 654 Stylosanthes_scabra Stylosanthes 0.000000e+00
## 655 Stylosanthes_viscosa Stylosanthes 7.249777e+10
## 656 Sutherlandia_frutescens Sutherlandia 4.900000e+12
## 657 Swainsona_formosa Swainsona 6.628851e+10
## 658 Swainsona_pterostylis <NA> NA
## 659 Swartzia_laevicarpa Swartzia 0.000000e+00
## 660 Swartzia_langsdorffii Swartzia 0.000000e+00
## 661 Swartzia_leptopetala Swartzia 0.000000e+00
## 662 Swartzia_polyphylla Swartzia 1.300000e+11
## 663 Swartzia_simplex Swartzia 0.000000e+00
## 664 Templetonia_retusa Templetonia 0.000000e+00
## 665 Tephrosia_grandiflora Tephrosia 8.130000e+11
## 666 Tephrosia_villosa Tephrosia 0.000000e+00
## 667 Teramnus_uncinatus Teramnus 0.000000e+00
## 668 Thermopsis_lanceolata Thermopsis 0.000000e+00
## 669 Thermopsis_lupinoides Thermopsis 0.000000e+00
## 670 Thermopsis_villosa Thermopsis 0.000000e+00
## 671 Tipuana_tipu Tipuana 1.490000e+13
## 672 Trifolium_africanum Trifolium 0.000000e+00
## 673 Trifolium_albopurpureum Trifolium 0.000000e+00
## 674 Trifolium_alexandrinum Trifolium 2.980000e+13
## 675 Trifolium_alpestre Trifolium 4.597801e+10
## 676 Trifolium_amabile Trifolium 0.000000e+00
## 677 Trifolium_ambiguum Trifolium 9.190000e+11
## 678 Trifolium_angustifolium Trifolium 8.580000e+12
## 679 Trifolium_argutum Trifolium 3.070000e+12
## 680 Trifolium_arvense <NA> NA
## 681 Trifolium_aureum Trifolium 1.050000e+12
## 682 Trifolium_baccarinii Trifolium 0.000000e+00
## 683 Trifolium_beckwithii Trifolium 0.000000e+00
## 684 Trifolium_bifidum Trifolium 0.000000e+00
## 685 Trifolium_bocconei Trifolium 3.580000e+11
## 686 Trifolium_boissieri Trifolium 0.000000e+00
## 687 Trifolium_burchellianum Trifolium 0.000000e+00
## 688 Trifolium_campestre Trifolium 4.090000e+13
## 689 Trifolium_cernuum Trifolium 1.280000e+13
## 690 Trifolium_cheranganiense Trifolium 2.670000e+12
## 691 Trifolium_cherleri Trifolium 3.510000e+12
## 692 Trifolium_ciliolatum Trifolium 0.000000e+00
## 693 Trifolium_clypeatum Trifolium 0.000000e+00
## 694 Trifolium_cyathiferum Trifolium 0.000000e+00
## 695 Trifolium_dasyphyllum Trifolium 0.000000e+00
## 696 Trifolium_depauperatum Trifolium 0.000000e+00
## 697 Trifolium_dubium Trifolium 4.030000e+13
## 698 Trifolium_echinatum Trifolium 7.950000e+11
## 699 Trifolium_fragiferum Trifolium 2.390000e+13
## 700 Trifolium_fucatum Trifolium 0.000000e+00
## 701 Trifolium_glanduliferum Trifolium 0.000000e+00
## 702 Trifolium_glomeratum Trifolium 1.410000e+13
## 703 Trifolium_gracilentum Trifolium 0.000000e+00
## 704 Trifolium_grandiflorum Trifolium 0.000000e+00
## 705 Trifolium_hirtum Trifolium 9.190000e+12
## 706 Trifolium_incarnatum Trifolium 3.160000e+13
## 707 Trifolium_lappaceum Trifolium 5.160000e+12
## 708 Trifolium_longipes Trifolium 0.000000e+00
## 709 Trifolium_micranthum Trifolium 6.520000e+12
## 710 Trifolium_microcephalum Trifolium 0.000000e+00
## 711 Trifolium_nanum Trifolium 0.000000e+00
## 712 Trifolium_nigrescens Trifolium 6.330000e+11
## 713 Trifolium_obscurum Trifolium 0.000000e+00
## 714 Trifolium_ornithopodioides Trifolium 7.550000e+12
## 715 Trifolium_palaestinum Trifolium 0.000000e+00
## 716 Trifolium_pallidum Trifolium 5.390000e+11
## 717 Trifolium_patens Trifolium 0.000000e+00
## 718 Trifolium_pratense <NA> NA
## 719 Trifolium_pseudostriatum Trifolium 0.000000e+00
## 720 Trifolium_reflexum Trifolium 0.000000e+00
## 721 Trifolium_repens Trifolium 6.310000e+13
## 722 Trifolium_resupinatum Trifolium 1.540000e+13
## 723 Trifolium_rubens Trifolium 0.000000e+00
## 724 Trifolium_rueppellianum Trifolium 9.160000e+11
## 725 Trifolium_scabrum Trifolium 4.720000e+12
## 726 Trifolium_scutatum Trifolium 0.000000e+00
## 727 Trifolium_semipilosum Trifolium 1.080000e+13
## 728 Trifolium_simense Trifolium 0.000000e+00
## 729 Trifolium_spumosum Trifolium 2.790000e+12
## 730 Trifolium_squamosum Trifolium 7.870000e+12
## 731 Trifolium_squarrosum Trifolium 5.990000e+11
## 732 Trifolium_stellatum Trifolium 4.040000e+12
## 733 Trifolium_stoloniferum Trifolium 0.000000e+00
## 734 Trifolium_striatum Trifolium 1.480000e+13
## 735 Trifolium_strictum Trifolium 3.580000e+11
## 736 Trifolium_suffocatum Trifolium 7.550000e+12
## 737 Trifolium_sylvaticum Trifolium 3.580000e+11
## 738 Trifolium_thalii Trifolium 0.000000e+00
## 739 Trifolium_tomentosum Trifolium 1.130000e+13
## 740 Trifolium_usambarense Trifolium 3.060000e+12
## 741 Trifolium_variegatum Trifolium 0.000000e+00
## 742 Trifolium_willdenovii Trifolium 0.000000e+00
## 743 Trifolium_wormskioldii Trifolium 0.000000e+00
## 744 Trigonella_arabica Trigonella 0.000000e+00
## 745 Trigonella_balansae Trigonella 1.160000e+11
## 746 Trigonella_caerulea Trigonella 4.380000e+13
## 747 Trigonella_calliceras Trigonella 0.000000e+00
## 748 Trigonella_cretica Trigonella 0.000000e+00
## 749 Trigonella_stellata Trigonella 0.000000e+00
## 750 Tripodion_tetraphyllum Tripodion 0.000000e+00
## 751 Ulex_europaeus Ulex 5.400000e+13
## 752 Ulex_gallii Ulex 0.000000e+00
## 753 Uraria_picta Uraria 2.055545e+09
## 754 Vandasina_retusa Vandasina 0.000000e+00
## 755 Vicia_americana Vicia 0.000000e+00
## 756 Vicia_amoena Vicia 0.000000e+00
## 757 Vicia_articulata Vicia 9.560000e+12
## 758 Vicia_benghalensis Vicia 6.650000e+12
## 759 Vicia_bithynica Vicia 0.000000e+00
## 760 Vicia_cassubica Vicia 0.000000e+00
## 761 Vicia_cracca <NA> NA
## 762 Vicia_disperma Vicia 9.090000e+12
## 763 Vicia_ervilia Vicia 4.070000e+12
## 764 Vicia_faba <NA> NA
## 765 Vicia_grandiflora Vicia 2.650000e+12
## 766 Vicia_hirsuta <NA> NA
## 767 Vicia_hybrida Vicia 4.150741e+10
## 768 Vicia_lathyroides Vicia 8.920000e+12
## 769 Vicia_ludoviciana Vicia 0.000000e+00
## 770 Vicia_lutea Vicia 3.840000e+12
## 771 Vicia_monantha Vicia 8.740000e+12
## 772 Vicia_narbonensis Vicia 1.650000e+13
## 773 Vicia_pannonica Vicia 1.410000e+13
## 774 Vicia_parviflora Vicia 6.628851e+10
## 775 Vicia_peregrina Vicia 4.600000e+11
## 776 Vicia_sativa <NA> NA
## 777 Vicia_sepium <NA> NA
## 778 Vicia_tenuifolia Vicia 2.840000e+11
## 779 Vicia_tetrasperma <NA> NA
## 780 Vicia_unijuga Vicia 0.000000e+00
## 781 Vicia_villosa Vicia 1.300000e+13
## 782 Vigna_angularis Vigna 5.000000e+12
## 783 Vigna_luteola Vigna 3.290000e+12
## 784 Vigna_marina Vigna 5.763480e+09
## 785 Vigna_mungo Vigna 1.980000e+13
## 786 Vigna_radiata <NA> NA
## 787 Vigna_subterranea Vigna 2.000000e+13
## 788 Vigna_trilobata Vigna 5.040000e+12
## 789 Vigna_unguiculata Vigna 1.880000e+13
## 790 Virgilia_divaricata <NA> NA
## 791 Virgilia_oroboides Virgilia 1.240000e+13
## 792 Wallaceodendron_celebicum Wallaceodendron 0.000000e+00
## 793 Wisteria_floribunda Wisteria 1.340000e+13
## 794 Wisteria_frutescens Wisteria 2.780000e+12
## 795 Wisteria_sinensis Wisteria 8.570000e+12
## 796 Xeroderris_stuhlmannii Xeroderris 0.000000e+00
## 797 Zapoteca_formosa Zapoteca 0.000000e+00
## areaIntroducedScale areaNative areaNativeScale Num_Introduced Fixer
## 1 -0.319851409 5.340000e+13 5.960221547 4 1
## 2 -0.338875120 3.330000e+12 -0.477883650 0 1
## 3 -0.338875120 2.530000e+12 -0.580749321 0 1
## 4 -0.338875120 3.880000e+12 -0.407163501 0 1
## 5 -0.338875120 9.340000e+12 0.294894705 0 1
## 6 1.100757094 4.090000e+12 -0.380161262 23 1
## 7 1.036487799 6.270000e+12 -0.099852308 13 1
## 8 -0.338875120 7.510000e+11 -0.809496857 0 1
## 9 -0.324093182 2.010000e+12 -0.647612007 1 1
## 10 -0.314581327 4.050000e+12 -0.385304546 1 1
## 11 -0.338710030 2.010000e+12 -0.647612007 1 1
## 12 -0.304426778 8.020000e+11 -0.802939171 2 1
## 13 -0.044521748 8.610000e+12 0.201029780 5 1
## 14 -0.338875120 5.010000e+12 -0.261865740 0 1
## 15 -0.338875120 1.730000e+12 -0.683614992 0 1
## 16 -0.338875120 5.610000e+12 -0.184716487 0 1
## 17 0.121293034 1.250000e+12 -0.745334395 13 1
## 18 2.334727564 2.530000e+12 -0.580749321 13 1
## 19 1.524934443 4.610000e+12 -0.313298576 28 1
## 20 -0.338875120 3.160000e+12 -0.499742605 0 1
## 21 0.946510786 6.400000e+12 -0.083136637 19 1
## 22 0.905378437 3.560000e+12 -0.448309769 11 1
## 23 -0.338875120 8.020000e+11 -0.802939171 0 1
## 24 -0.304426778 2.760000e+12 -0.551175441 2 1
## 25 -0.338875120 6.240000e+12 -0.103709771 0 1
## 26 -0.338875120 1.500000e+13 1.022669329 0 1
## 27 -0.338875120 2.530000e+12 -0.580749321 0 1
## 28 -0.338875120 1.750000e+13 1.344124552 0 1
## 29 -0.304426778 2.760000e+12 -0.551175441 2 1
## 30 0.717712094 6.520000e+12 -0.067706786 10 1
## 31 -0.338875120 9.130000e+12 0.267892467 0 1
## 32 -0.327938899 1.685873e+10 -0.903894275 2 1
## 33 -0.338875120 2.530000e+12 -0.580749321 0 1
## 34 -0.338875120 2.530000e+12 -0.580749321 0 1
## 35 -0.338875120 7.620000e+12 0.073733512 0 1
## 36 2.296165986 3.810000e+12 -0.416164247 20 1
## 37 1.949111792 6.750000e+12 -0.038132905 34 1
## 38 1.859134779 6.340000e+12 -0.090851562 26 1
## 39 -0.338875120 5.440000e+12 -0.206575442 0 1
## 40 -0.338875120 7.060000e+12 0.001727542 0 1
## 41 0.285822430 3.070000e+13 3.041408127 21 1
## 42 -0.314581327 2.010000e+12 -0.647612007 1 1
## 43 -0.338875120 3.510000e+12 -0.454738874 0 1
## 44 0.212555433 6.270000e+12 -0.099852308 8 1
## 45 2.566097027 6.170000e+12 -0.112710517 13 1
## 46 -0.335556308 2.290000e+13 2.038467832 8 1
## 47 -0.338875120 8.020000e+11 -0.802939171 0 1
## 48 -0.287716761 2.530000e+12 -0.580749321 3 1
## 49 -0.338875120 4.390000e+12 -0.341586635 0 1
## 50 2.270458268 6.270000e+12 -0.099852308 21 1
## 51 0.873243789 2.720000e+13 2.591370815 3 1
## 52 0.125149192 1.790000e+13 1.395557387 3 1
## 53 -0.029097117 2.660000e+12 -0.564033649 2 1
## 54 -0.314581327 1.210000e+12 -0.750477679 1 1
## 55 -0.066373308 3.940000e+12 -0.399448575 1 1
## 56 -0.297871310 1.100000e+12 -0.764621708 1 1
## 57 -0.338875120 7.390000e+12 0.044159632 0 1
## 58 0.091729158 2.520000e+13 2.334206637 4 1
## 59 -0.338875120 2.760000e+12 -0.551175441 0 1
## 60 -0.045807134 2.080000e+12 -0.638611261 6 1
## 61 -0.338875120 7.620000e+12 0.073733512 0 1
## 62 -0.338875120 6.140000e+12 -0.116567980 0 1
## 63 -0.338875120 1.990000e+12 -0.650183649 0 1
## 64 -0.338875120 1.120000e+12 -0.762050067 0 1
## 65 -0.338875120 2.620000e+12 -0.569176933 0 1
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## 67 -0.338875120 3.210000e+12 -0.493313500 0 1
## 68 -0.338875120 7.521102e+09 -0.905094927 0 1
## 69 -0.338875120 1.640000e+13 1.202684254 0 1
## 70 1.357834275 2.630000e+13 2.475646935 24 1
## 71 -0.338875120 8.600000e+12 0.199743959 0 1
## 72 -0.192341127 NA NA 1 1
## 73 -0.331488137 4.640000e+13 5.060146924 8 1
## 74 -0.338875120 NA NA 0 1
## 75 -0.120359516 1.280000e+11 -0.889603499 3 1
## 76 NA NA NA NA 1
## 77 -0.338875120 1.300000e+13 0.765505151 0 1
## 78 -0.338389274 1.740000e+13 1.331266343 2 1
## 79 -0.338875120 7.760000e+11 -0.806282305 0 1
## 80 -0.235015939 4.310000e+12 -0.351873203 2 1
## 81 3.568698033 1.730000e+13 1.318408134 19 1
## 82 -0.338875120 8.990000e+12 0.249890974 0 1
## 83 5.651023200 9.600000e+12 0.328326048 55 1
## 84 -0.338875120 5.160000e+12 -0.242578427 0 1
## 85 1.769157765 1.180000e+13 0.611206644 14 1
## 86 -0.338875120 9.350000e+12 0.296180526 0 1
## 87 -0.338875120 NA NA 0 1
## 88 -0.338875120 3.200000e+12 -0.494599321 0 1
## 89 -0.338875120 7.680000e+11 -0.807310962 0 1
## 90 -0.338875120 1.730000e+13 1.318408134 0 1
## 91 2.746051053 1.810000e+13 1.421273805 24 1
## 92 -0.338875120 1.910000e+13 1.549855894 0 1
## 93 -0.338875120 2.670000e+12 -0.562747829 0 1
## 94 -0.338875120 2.670000e+12 -0.562747829 0 1
## 95 -0.338610903 NA NA 1 1
## 96 NA NA NA NA 1
## 97 0.026174477 2.280000e+13 2.025609623 6 1
## 98 -0.338875120 9.850000e+11 -0.779408649 0 1
## 99 -0.338875120 4.030000e+11 -0.854243424 0 1
## 100 -0.338875120 4.480000e+12 -0.330014247 0 1
## 101 NA 3.852705e-01 -0.906062006 2 1
## 102 -0.338875120 8.710000e+12 0.213887989 0 1
## 103 -0.338875120 2.830000e+12 -0.542174694 0 1
## 104 -0.143496463 1.760000e+13 1.356982761 2 1
## 105 7.849033099 1.200000e+13 0.636923062 67 1
## 106 NA NA NA NA 1
## 107 -0.338875120 4.570000e+12 -0.318441859 0 1
## 108 -0.338875120 2.670000e+12 -0.562747829 0 1
## 109 -0.338875120 2.670000e+12 -0.562747829 0 1
## 110 -0.338875120 2.670000e+12 -0.562747829 0 1
## 111 -0.338875120 4.340000e+13 4.674400657 0 1
## 112 -0.338875120 1.700000e+12 -0.687472455 0 1
## 113 -0.338875120 1.100000e+12 -0.764621708 0 1
## 114 -0.338875120 1.280000e+13 0.739788733 0 1
## 115 -0.338875120 1.000000e+13 0.379758884 0 1
## 116 -0.338875120 2.210000e+13 1.935602161 0 1
## 117 0.014606004 1.570000e+13 1.112676791 6 1
## 118 -0.338875120 1.170000e+13 0.598348435 0 1
## 119 -0.338875120 7.130000e+12 0.010728288 0 1
## 120 -0.338875120 1.540000e+12 -0.708045589 0 1
## 121 -0.338875120 5.090000e+12 -0.251579173 0 1
## 122 -0.338875120 2.320000e+12 -0.607751560 0 1
## 123 -0.338875120 2.120000e+12 -0.633467978 0 1
## 124 -0.338875120 9.220000e+12 0.279464855 0 1
## 125 -0.338875120 6.090000e+11 -0.827755514 0 1
## 126 -0.309182706 6.070000e+12 -0.125568726 1 1
## 127 -0.338875120 NA NA 0 1
## 128 -0.338875120 1.250000e+13 0.701214107 0 1
## 129 -0.338875120 3.440000e+12 -0.463739620 0 1
## 130 -0.338875120 1.920000e+12 -0.659184395 0 1
## 131 -0.338875120 1.250000e+13 0.701214107 0 1
## 132 -0.338875120 2.750000e+12 -0.552461261 0 1
## 133 -0.338875120 1.280000e+13 0.739788733 0 1
## 134 -0.338875120 1.840000e+13 1.459848432 0 1
## 135 -0.338875120 1.220000e+13 0.662639480 0 1
## 136 -0.338875120 1.050000e+13 0.444049928 0 1
## 137 -0.338875120 1.760000e+13 1.356982761 0 1
## 138 1.409249712 1.090000e+13 0.495482764 2 1
## 139 -0.338875120 3.470000e+12 -0.459882157 0 1
## 140 -0.338875120 1.110000e+13 0.521199182 0 1
## 141 -0.030382503 6.280000e+12 -0.098566487 3 1
## 142 -0.321908026 7.970000e+12 0.118737243 2 1
## 143 -0.319979947 1.550000e+13 1.086960374 1 1
## 144 0.134146893 5.310000e+12 -0.223291114 5 1
## 145 -0.338875120 2.530000e+12 -0.580749321 0 1
## 146 -0.338875120 1.130000e+13 0.546915600 0 1
## 147 -0.283603526 1.210000e+11 -0.890503573 4 1
## 148 -0.338875120 5.320000e+12 -0.222005293 0 1
## 149 5.573900046 6.610000e+12 -0.056134398 67 1
## 150 -0.338875120 7.410000e+11 -0.810782678 0 1
## 151 -0.338875120 3.660000e+12 -0.435451560 0 1
## 152 -0.058660993 2.870000e+12 -0.537031411 7 1
## 153 -0.057375607 1.830000e+13 1.446990223 2 1
## 154 -0.242985332 1.180000e+13 0.611206644 1 1
## 155 -0.338875120 5.120000e+12 -0.247721710 0 1
## 156 -0.319979947 1.770000e+13 1.369840969 1 1
## 157 -0.336708123 2.050000e+13 1.729870819 1 1
## 158 3.183082261 9.060000e+12 0.258891720 26 1
## 159 -0.338842636 5.300000e+13 5.908788712 1 1
## 160 -0.338875120 3.610000e+12 -0.441880665 0 1
## 161 -0.338875120 3.400000e+12 -0.468882904 0 1
## 162 -0.169204181 8.010000e+12 0.123880527 3 1
## 163 -0.338875120 1.530000e+11 -0.886388947 0 1
## 164 -0.338875120 1.530000e+11 -0.886388947 0 1
## 165 NA -9.010859e-01 -0.906062006 4 1
## 166 -0.338875120 2.080000e+12 -0.638611261 0 1
## 167 2.887443503 2.110000e+13 1.807020072 31 1
## 168 -0.267664741 1.100000e+13 0.508340973 5 1
## 169 -0.338875120 5.930000e+11 -0.829812827 0 1
## 170 -0.338610903 1.220000e+13 0.662639480 1 1
## 171 -0.061231765 1.370000e+13 0.855512613 5 1
## 172 -0.338875120 2.530000e+12 -0.580749321 0 1
## 173 9.185834441 7.460000e+12 0.053160378 48 1
## 174 -0.338875120 1.190000e+12 -0.753049320 0 1
## 175 -0.338875120 1.400000e+12 -0.726047082 0 1
## 176 -0.338875120 7.560000e+11 -0.808853947 0 1
## 177 -0.292472689 1.150000e+11 -0.891275066 2 1
## 178 1.165026389 2.670000e+12 -0.562747829 16 1
## 179 -0.338875120 9.850000e+12 0.360471571 0 1
## 180 -0.338875120 4.630000e+12 -0.310726934 0 1
## 181 -0.338875120 4.290000e+12 -0.354444844 0 1
## 182 -0.338875120 5.540000e+12 -0.193717233 0 1
## 183 0.681721289 2.370000e+13 2.141333504 1 1
## 184 -0.338875120 1.650000e+12 -0.693901559 0 1
## 185 -0.338875120 6.190000e+12 -0.110138875 0 1
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## 187 -0.338875120 3.790000e+13 3.967199168 0 1
## 188 -0.229874395 3.980000e+12 -0.394305292 5 1
## 189 -0.338875120 1.450000e+13 0.958378285 0 1
## 190 -0.338875120 1.480000e+12 -0.715760514 0 1
## 191 2.360435282 1.920000e+13 1.562714103 8 1
## 192 1.499226725 2.930000e+12 -0.529316485 20 1
## 193 -0.071514852 1.080000e+13 0.482624555 4 1
## 194 1.280711121 1.960000e+13 1.614146939 9 1
## 195 1.884842497 3.480000e+13 3.568594692 37 1
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## 200 -0.338875120 4.050000e+12 -0.385304546 0 1
## 201 1.692034611 1.310000e+11 -0.889217753 18 1
## 202 NA NA NA NA 1
## 203 -0.338875120 2.670000e+12 -0.562747829 0 1
## 204 NA NA NA NA 1
## 205 NA NA NA NA 1
## 206 -0.338875120 2.720000e+12 -0.556318724 0 1
## 207 NA NA NA NA 1
## 208 NA -6.716556e-01 -0.906062006 27 1
## 209 NA -1.007745e+00 -0.906062006 4 1
## 210 -0.338875120 5.380000e+12 -0.214290367 0 1
## 211 -0.264065660 3.960000e+12 -0.396876934 1 1
## 212 -0.338875120 1.050000e+13 0.444049928 0 1
## 213 -0.202624214 2.180000e+13 1.897027534 4 1
## 214 -0.338875120 3.570000e+12 -0.447023948 0 1
## 215 -0.338875120 8.950000e+12 0.244747690 0 1
## 216 -0.338875120 1.480000e+12 -0.715760514 0 1
## 217 1.794865483 1.100000e+13 0.508340973 14 1
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## 239 3.414451724 1.340000e+13 0.816937987 28 1
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## 261 -0.338796200 3.700000e+13 3.851475288 1 1
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## 274 -0.338875120 1.550000e+12 -0.706759768 0 1
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## 278 -0.338875120 1.570000e+13 1.112676791 0 1
## 279 11.062497860 1.060000e+13 0.456908137 50 1
## 280 -0.338875120 2.830000e+12 -0.542174694 0 1
## 281 -0.264065660 8.440000e+12 0.179170825 1 1
## 282 1.640619175 2.460000e+13 2.257057384 9 1
## 283 -0.338875120 1.940000e+13 1.588430521 0 1
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## 611 -0.338875120 8.020000e+11 -0.802939171 0 1
## 612 -0.338875120 3.810000e+12 -0.416164247 0 1
## 613 -0.338875120 2.530000e+12 -0.580749321 0 1
## 614 1.049341658 4.230000e+12 -0.362159770 4 1
## 615 -0.153779550 8.040000e+12 0.127737989 2 1
## 616 0.032601407 3.460000e+12 -0.461167978 2 1
## 617 -0.336708123 5.910000e+13 6.693139455 1 1
## 618 0.528760366 2.460000e+12 -0.589750067 11 1
## 619 4.494175885 2.070000e+13 1.755587236 26 1
## 620 0.675294359 1.390000e+12 -0.727332902 9 1
## 621 -0.304426778 1.560000e+13 1.099818582 2 1
## 622 0.914376138 5.560000e+12 -0.191145591 4 1
## 623 3.504428738 1.830000e+13 1.446990223 15 1
## 624 0.518477279 1.030000e+13 0.418333511 9 1
## 625 -0.338875120 1.270000e+12 -0.742762753 0 1
## 626 1.910550215 2.380000e+12 -0.600036634 39 1
## 627 -0.338875120 2.690000e+12 -0.560176187 0 1
## 628 0.346235568 2.780000e+12 -0.548603799 9 1
## 629 0.914376138 4.170000e+13 4.455811106 11 1
## 630 -0.338875120 1.230000e+13 0.675497689 0 1
## 631 -0.338875120 NA NA 0 1
## 632 -0.202624214 1.240000e+13 0.688355898 4 1
## 633 -0.338875120 2.940000e+11 -0.868258872 0 1
## 634 -0.338875120 1.685873e+10 -0.903894275 0 1
## 635 0.078875299 3.550000e+12 -0.449595590 2 1
## 636 -0.309182706 1.900000e+13 1.536997685 1 1
## 637 0.778125232 2.680000e+11 -0.871602006 2 1
## 638 -0.309182706 1.530000e+11 -0.886388947 1 1
## 639 -0.079227167 1.070000e+12 -0.768479171 3 1
## 640 -0.338875120 1.150000e+11 -0.891275066 0 1
## 641 0.121293034 2.640000e+13 2.488505144 2 1
## 642 NA NA NA NA 1
## 643 -0.309439783 2.950000e+11 -0.868130290 6 1
## 644 -0.338875120 3.000000e+12 -0.520315739 0 1
## 645 -0.338875120 NA NA 0 1
## 646 -0.338875120 NA NA 0 1
## 647 -0.338875120 2.500000e+12 -0.584606784 0 1
## 648 -0.338875120 9.930000e+12 0.370758138 0 1
## 649 -0.338875120 2.700000e+13 2.565654397 0 1
## 650 2.116211960 5.220000e+12 -0.234863502 23 1
## 651 -0.303527008 NA NA 2 1
## 652 1.280711121 3.840000e+12 -0.412306784 14 1
## 653 -0.338875120 NA NA 0 1
## 654 -0.338875120 NA NA 0 1
## 655 -0.329556359 1.280000e+11 -0.889603499 1 1
## 656 0.290963974 4.080000e+12 -0.381447083 3 1
## 657 -0.330354488 7.390000e+12 0.044159632 1 1
## 658 NA NA NA NA 1
## 659 -0.338875120 6.800000e+12 -0.031703801 0 1
## 660 -0.338875120 NA NA 0 1
## 661 -0.338875120 NA NA 0 1
## 662 -0.322165103 NA NA 1 1
## 663 -0.338875120 4.820000e+11 -0.844085439 0 1
## 664 -0.338875120 3.510000e+12 -0.454738874 0 1
## 665 -0.234373246 2.670000e+12 -0.562747829 2 1
## 666 -0.338875120 2.570000e+13 2.398497682 0 1
## 667 -0.338875120 3.170000e+13 3.169990216 0 1
## 668 -0.338875120 5.520000e+12 -0.196288875 0 1
## 669 -0.338875120 7.380000e+12 0.042873811 0 1
## 670 -0.338875120 9.470000e+11 -0.784294768 0 1
## 671 1.576349879 1.320000e+12 -0.736333649 11 1
## 672 -0.338875120 2.700000e+12 -0.558890366 0 1
## 673 -0.338875120 1.620000e+13 1.176967836 0 1
## 674 3.491574879 1.310000e+11 -0.889217753 25 1
## 675 -0.332965171 1.280000e+13 0.739788733 1 1
## 676 -0.338875120 9.700000e+12 0.341184257 0 1
## 677 -0.220748155 8.600000e+12 0.199743959 2 1
## 678 0.763985987 1.110000e+13 0.521199182 9 1
## 679 0.055738353 2.070000e+12 -0.639897082 2 1
## 680 NA 1.429307e+00 -0.906062006 13 1
## 681 -0.203909600 2.260000e+13 1.999893206 7 1
## 682 -0.338875120 6.620000e+12 -0.054848577 0 1
## 683 -0.338875120 1.960000e+12 -0.654041112 0 1
## 684 -0.338875120 8.340000e+11 -0.798824544 0 1
## 685 -0.292858305 6.060000e+12 -0.126854547 1 1
## 686 -0.338875120 1.650000e+12 -0.693901559 0 1
## 687 -0.338875120 6.830000e+12 -0.027846338 0 1
## 688 4.918353234 3.560000e+13 3.671460363 20 1
## 689 1.306418839 1.540000e+12 -0.708045589 15 1
## 690 0.004322917 8.240000e+11 -0.800110365 1 1
## 691 0.112295333 9.630000e+12 0.332183511 1 1
## 692 -0.338875120 8.340000e+11 -0.798824544 0 1
## 693 -0.338875120 1.090000e+12 -0.765907529 0 1
## 694 -0.338875120 4.620000e+12 -0.312012755 0 1
## 695 -0.338875120 1.440000e+12 -0.720903798 0 1
## 696 -0.338875120 3.880000e+12 -0.407163501 0 1
## 697 4.841230080 1.300000e+13 0.765505151 33 1
## 698 -0.236686941 6.240000e+12 -0.103709771 1 1
## 699 2.733197194 3.470000e+13 3.555736483 7 1
## 700 -0.338875120 8.340000e+11 -0.798824544 0 1
## 701 -0.338875120 1.220000e+12 -0.749191858 0 1
## 702 1.473519007 8.450000e+12 0.180456646 12 1
## 703 -0.338875120 1.680000e+13 1.254117089 0 1
## 704 -0.338875120 3.970000e+12 -0.395591113 0 1
## 705 0.842394527 8.070000e+12 0.131595452 7 1
## 706 3.722944342 5.030000e+12 -0.259294098 28 1
## 707 0.324384007 1.100000e+13 0.508340973 2 1
## 708 -0.338875120 1.340000e+12 -0.733762007 0 1
## 709 0.499196490 1.080000e+13 0.482624555 5 1
## 710 -0.338875120 4.540000e+12 -0.322299322 0 1
## 711 -0.338875120 1.440000e+12 -0.720903798 0 1
## 712 -0.257510192 8.930000e+12 0.242176049 1 1
## 713 -0.338875120 3.550000e+12 -0.449595590 0 1
## 714 0.631591239 5.420000e+12 -0.209147084 6 1
## 715 -0.338875120 3.140000e+11 -0.865687230 0 1
## 716 -0.269592820 5.320000e+12 -0.222005293 1 1
## 717 -0.338875120 5.200000e+12 -0.237435143 0 1
## 718 NA 1.390639e+00 -0.906062006 27 1
## 719 -0.338875120 3.680000e+12 -0.432879919 0 1
## 720 -0.338875120 1.900000e+13 1.536997685 0 1
## 721 7.771909945 4.120000e+13 4.391520061 39 1
## 722 1.640619175 1.210000e+13 0.649781271 16 1
## 723 -0.338875120 3.690000e+12 -0.431594098 0 1
## 724 -0.221133771 9.120000e+12 0.266606646 4 1
## 725 0.267827027 1.290000e+13 0.752646942 3 1
## 726 -0.338875120 1.620000e+12 -0.697759022 0 1
## 727 1.049341658 3.070000e+12 -0.511314993 4 1
## 728 -0.338875120 9.130000e+12 0.267892467 0 1
## 729 0.019747548 8.720000e+12 0.215173810 3 1
## 730 0.672723588 8.820000e+12 0.228032019 3 1
## 731 -0.261880504 6.450000e+12 -0.076707532 2 1
## 732 0.180420786 1.060000e+13 0.456908137 3 1
## 733 -0.338875120 1.060000e+12 -0.769764992 0 1
## 734 1.563496020 1.460000e+13 0.971236493 6 1
## 735 -0.292858305 6.740000e+12 -0.039418726 1 1
## 736 0.631591239 9.740000e+12 0.346327541 5 1
## 737 -0.292858305 3.750000e+12 -0.423879172 1 1
## 738 -0.338875120 2.170000e+12 -0.627038873 0 1
## 739 1.113610953 1.500000e+13 1.022669329 9 1
## 740 0.054452967 8.300000e+12 0.161169333 2 1
## 741 -0.338875120 1.810000e+13 1.421273805 0 1
## 742 -0.338875120 1.950000e+12 -0.655326933 0 1
## 743 -0.338875120 3.700000e+12 -0.430308277 0 1
## 744 -0.338875120 1.300000e+12 -0.738905291 0 1
## 745 -0.323964644 3.270000e+12 -0.485598575 1 1
## 746 5.291115147 NA NA 15 1
## 747 -0.338875120 2.250000e+12 -0.616752306 0 1
## 748 -0.338875120 7.620000e+11 -0.808082454 0 1
## 749 -0.338875120 1.020000e+13 0.405475302 0 1
## 750 -0.338875120 8.380000e+12 0.171455900 0 1
## 751 6.602208771 2.250000e+12 -0.616752306 40 1
## 752 -0.338875120 1.330000e+12 -0.735047828 0 1
## 753 -0.338610903 3.110000e+13 3.092840962 1 1
## 754 -0.338875120 4.670000e+12 -0.305583651 0 1
## 755 -0.338875120 5.920000e+12 -0.144856039 0 1
## 756 -0.338875120 1.980000e+13 1.639863356 0 1
## 757 0.889953806 3.800000e+12 -0.417450068 4 1
## 758 0.515906507 4.430000e+12 -0.336443352 7 1
## 759 -0.338875120 7.270000e+12 0.028729781 0 1
## 760 -0.338875120 1.230000e+13 0.675497689 0 1
## 761 NA 1.616203e+00 -0.906062006 9 1
## 762 0.829540668 4.310000e+12 -0.351873203 3 1
## 763 0.184276943 1.280000e+13 0.739788733 6 1
## 764 NA -1.052922e+00 -0.906062006 45 1
## 765 0.001752145 1.130000e+13 0.546915600 2 1
## 766 NA 1.654871e+00 -0.906062006 16 1
## 767 -0.333539816 1.920000e+13 1.562714103 1 1
## 768 0.807689108 1.170000e+13 0.598348435 6 1
## 769 -0.338875120 3.180000e+12 -0.497170963 0 1
## 770 0.154713068 1.150000e+13 0.572632018 6 1
## 771 0.784552161 1.350000e+13 0.829796196 3 1
## 772 1.782011624 1.740000e+13 1.331266343 5 1
## 773 1.473519007 1.110000e+13 0.521199182 10 1
## 774 -0.330354488 1.060000e+13 0.456908137 1 1
## 775 -0.279747369 2.390000e+13 2.167049921 3 1
## 776 NA 1.339283e-01 -0.906062006 39 1
## 777 NA NA NA NA 1
## 778 -0.302370160 3.040000e+13 3.002833500 3 1
## 779 NA 1.339082e+00 -0.906062006 11 1
## 780 -0.338875120 2.450000e+13 2.244199175 0 1
## 781 1.332126557 2.920000e+13 2.848534993 12 1
## 782 0.303817833 3.260000e+11 -0.864144245 11 1
## 783 0.084016843 2.490000e+13 2.295632010 6 1
## 784 -0.338134291 8.320000e+12 0.163740974 4 1
## 785 2.206188973 2.850000e+12 -0.539603053 16 1
## 786 NA -6.626331e-01 -0.906062006 36 1
## 787 2.231896691 2.310000e+12 -0.609037381 10 1
## 788 0.308959376 1.940000e+13 1.588430521 6 1
## 789 2.077650383 2.090000e+13 1.781303654 30 1
## 790 NA NA NA NA 1
## 791 1.255003403 2.670000e+12 -0.562747829 8 1
## 792 -0.338875120 2.600000e+12 -0.571748575 0 1
## 793 1.383541993 3.710000e+11 -0.858358051 6 1
## 794 0.018462162 1.630000e+12 -0.696473201 1 1
## 795 0.762700601 1.350000e+12 -0.732476186 24 1
## 796 -0.338875120 1.230000e+13 0.675497689 0 1
## 797 -0.338875120 6.100000e+12 -0.121711263 0 1
## numOTUs numGenera Specialist Human_Uses AbsLatNative LatNative
## 1 NA 1 1 7 9.00301812 9.00301812
## 2 NA <NA> <NA> 2 28.81814120 -28.81814120
## 3 NA <NA> <NA> 0 25.46607155 -25.46607155
## 4 NA <NA> <NA> 0 23.42045320 -23.42045320
## 5 NA <NA> <NA> 1 8.51803986 -8.51803986
## 6 NA 1 1 4 5.85860106 -5.85860106
## 7 NA <NA> <NA> 2 26.80596132 -26.80596132
## 8 NA <NA> <NA> 0 25.31401375 25.31401375
## 9 NA <NA> <NA> 0 31.74043124 -31.74043124
## 10 NA <NA> <NA> 0 21.71309195 -21.71309195
## 11 NA <NA> <NA> 1 31.74043124 -31.74043124
## 12 NA <NA> <NA> 1 32.17021086 -32.17021086
## 13 NA <NA> <NA> 4 22.36270805 22.36270805
## 14 NA <NA> <NA> 0 27.21964295 -27.21964295
## 15 NA <NA> <NA> 1 22.57378083 -22.57378083
## 16 NA <NA> <NA> 3 23.16077529 -23.16077529
## 17 NA <NA> <NA> 3 21.89229771 21.89229771
## 18 NA <NA> <NA> 1 25.79163463 -25.79163463
## 19 NA <NA> <NA> 6 35.13929898 -35.13929898
## 20 NA <NA> <NA> 1 16.73557126 -16.73557126
## 21 NA <NA> <NA> 4 17.04729784 -17.04729784
## 22 NA <NA> <NA> 1 29.35867544 -29.35867544
## 23 NA <NA> <NA> 0 32.17021086 -32.17021086
## 24 NA <NA> <NA> 2 26.81043334 -26.81043334
## 25 NA <NA> <NA> 0 20.01409488 -20.01409488
## 26 NA <NA> <NA> 0 16.42384857 -16.42384857
## 27 NA <NA> <NA> 0 25.46607155 -25.46607155
## 28 NA <NA> <NA> 0 11.67782942 11.67782942
## 29 NA <NA> <NA> 1 26.80239184 -26.80239184
## 30 NA <NA> <NA> 7 24.27751659 -24.27751659
## 31 NA <NA> <NA> 0 3.77832300 3.77832300
## 32 NA <NA> <NA> 0 20.26898313 20.26898313
## 33 NA <NA> <NA> 0 25.79163463 -25.79163463
## 34 NA <NA> <NA> 0 25.79163463 -25.79163463
## 35 NA <NA> <NA> 1 25.55398159 -25.55398159
## 36 NA <NA> <NA> 1 34.81475557 -34.81475557
## 37 NA 1 1 5 25.13916559 -25.13916559
## 38 NA 1 1 4 34.37437305 -34.37437305
## 39 NA <NA> <NA> 3 22.67013251 22.67013251
## 40 NA <NA> <NA> 0 20.76721650 -20.76721650
## 41 NA <NA> <NA> 6 17.54782283 17.54782283
## 42 NA <NA> <NA> 0 31.74043124 -31.74043124
## 43 NA <NA> <NA> 0 26.80243548 -26.80243548
## 44 NA <NA> <NA> 2 26.80596132 -26.80596132
## 45 NA <NA> <NA> 1 11.17061857 -11.17061857
## 46 NA <NA> <NA> 2 7.27375193 7.27375193
## 47 NA <NA> <NA> 1 32.17021086 -32.17021086
## 48 NA <NA> <NA> 1 25.46607155 -25.46607155
## 49 NA <NA> <NA> 0 21.60644316 -21.60644316
## 50 NA 3 0 6 26.80241625 -26.80241625
## 51 NA <NA> <NA> 7 12.45705244 12.45705244
## 52 NA <NA> <NA> 5 16.45877917 16.45877917
## 53 NA <NA> <NA> 1 16.54013450 -16.54013450
## 54 NA <NA> <NA> 0 31.45395160 -31.45395160
## 55 NA <NA> <NA> 1 25.63938184 -25.63938184
## 56 NA <NA> <NA> 1 37.59703205 -37.59703205
## 57 NA <NA> <NA> 2 25.16284830 -25.16284830
## 58 NA <NA> <NA> 7 7.84844836 7.84844836
## 59 NA <NA> <NA> 0 26.80239184 -26.80239184
## 60 NA <NA> <NA> 1 36.84160801 -36.84160801
## 61 NA <NA> <NA> 3 25.55398159 -25.55398159
## 62 NA <NA> <NA> 0 11.66992496 -11.66992496
## 63 NA <NA> <NA> 0 38.70713460 38.70713460
## 64 NA <NA> <NA> 0 41.08761401 41.08761401
## 65 NA <NA> <NA> 0 31.95131923 31.95131923
## 66 NA <NA> <NA> 1 36.55830366 36.55830366
## 67 NA <NA> <NA> 1 34.56156123 34.56156123
## 68 NA <NA> <NA> 1 28.33813027 28.33813027
## 69 NA 1 1 1 0.82786884 -0.82786884
## 70 NA 1 1 4 6.39935826 6.39935826
## 71 NA 1 1 0 1.03371626 1.03371626
## 72 NA <NA> <NA> 0 NA NA
## 73 NA 1 1 8 11.15298163 11.15298163
## 74 NA <NA> <NA> 0 NA NA
## 75 NA 1 1 0 12.83971200 12.83971200
## 76 NA 1 1 NA NA NA
## 77 NA <NA> <NA> 0 7.96008943 7.96008943
## 78 NA 1 1 0 0.91210461 0.91210461
## 79 NA <NA> <NA> 0 35.02338879 35.02338879
## 80 NA <NA> <NA> 1 6.25866759 6.25866759
## 81 NA <NA> <NA> 5 27.01483409 27.01483409
## 82 NA <NA> <NA> 0 30.47597992 30.47597992
## 83 NA <NA> <NA> 9 11.73152247 11.73152247
## 84 NA <NA> <NA> 5 1.29421849 -1.29421849
## 85 NA <NA> <NA> 5 8.77720443 8.77720443
## 86 NA 1 1 3 43.35612615 43.35612615
## 87 NA <NA> <NA> 0 NA NA
## 88 NA 4 0 0 42.77144618 42.77144618
## 89 NA <NA> <NA> 0 27.58193304 27.58193304
## 90 NA <NA> <NA> 0 54.20867293 54.20867293
## 91 NA 2 0 1 34.25752634 34.25752634
## 92 NA 1 1 0 40.19097826 40.19097826
## 93 NA <NA> <NA> 0 25.48651667 -25.48651667
## 94 NA <NA> <NA> 0 25.48651667 -25.48651667
## 95 NA <NA> <NA> 0 NA NA
## 96 NA 1 1 NA NA NA
## 97 NA <NA> <NA> 6 9.47607629 9.47607629
## 98 NA <NA> <NA> 0 36.08495238 36.08495238
## 99 NA <NA> <NA> 0 31.88356133 31.88356133
## 100 NA <NA> <NA> 0 39.96671939 39.96671939
## 101 7 <NA> <NA> 3 42.22690675 42.22690675
## 102 NA <NA> <NA> 0 1.71495961 1.71495961
## 103 NA <NA> <NA> 1 34.37258831 -34.37258831
## 104 NA <NA> <NA> 2 51.04190951 51.04190951
## 105 NA 2 0 7 5.36188821 -5.36188821
## 106 NA 1 1 NA NA NA
## 107 NA <NA> <NA> 0 39.95072343 39.95072343
## 108 NA <NA> <NA> 0 25.48651667 -25.48651667
## 109 NA <NA> <NA> 0 25.48651667 -25.48651667
## 110 NA <NA> <NA> 0 25.48651667 -25.48651667
## 111 NA <NA> <NA> 3 50.50480983 50.50480983
## 112 NA <NA> <NA> 0 33.95816113 33.95816113
## 113 NA <NA> <NA> 0 43.82268732 43.82268732
## 114 NA <NA> <NA> 0 2.61975671 -2.61975671
## 115 NA <NA> <NA> 1 36.63369143 36.63369143
## 116 NA <NA> <NA> 0 50.81115160 50.81115160
## 117 NA <NA> <NA> 3 48.64765782 48.64765782
## 118 NA <NA> <NA> 2 37.51944817 37.51944817
## 119 NA <NA> <NA> 0 36.77551761 36.77551761
## 120 NA <NA> <NA> 0 43.14909047 43.14909047
## 121 NA <NA> <NA> 0 45.42187024 45.42187024
## 122 NA <NA> <NA> 0 42.08428343 42.08428343
## 123 NA <NA> <NA> 0 36.49303904 36.49303904
## 124 NA <NA> <NA> 0 42.53155377 42.53155377
## 125 NA <NA> <NA> 0 34.36209004 34.36209004
## 126 NA <NA> <NA> 0 40.88179525 40.88179525
## 127 NA <NA> <NA> 0 NA NA
## 128 NA 2 0 1 47.07382447 47.07382447
## 129 NA <NA> <NA> 1 26.06009224 26.06009224
## 130 NA <NA> <NA> 0 43.54344311 43.54344311
## 131 NA <NA> <NA> 2 49.97005713 49.97005713
## 132 NA <NA> <NA> 0 42.43797609 42.43797609
## 133 NA <NA> <NA> 2 38.23611007 38.23611007
## 134 NA <NA> <NA> 3 52.28284247 52.28284247
## 135 NA <NA> <NA> 1 58.41555631 58.41555631
## 136 NA <NA> <NA> 0 18.57377333 -18.57377333
## 137 NA <NA> <NA> 0 53.69006494 53.69006494
## 138 NA <NA> <NA> 0 38.25573071 38.25573071
## 139 NA <NA> <NA> 0 37.69622659 37.69622659
## 140 NA <NA> <NA> 0 43.10744572 43.10744572
## 141 NA <NA> <NA> 5 26.10273350 26.10273350
## 142 NA <NA> <NA> 2 37.79856088 37.79856088
## 143 NA <NA> <NA> 3 8.00369318 -8.00369318
## 144 NA <NA> <NA> 3 21.46859611 -21.46859611
## 145 NA <NA> <NA> 1 25.46607155 -25.46607155
## 146 NA <NA> <NA> 0 5.92922206 -5.92922206
## 147 NA <NA> <NA> 2 19.88572709 19.88572709
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## 523 NA <NA> <NA> 2 8.17614923 8.17614923
## 524 NA <NA> <NA> 1 11.89659651 11.89659651
## 525 NA <NA> <NA> 0 19.15791531 19.15791531
## 526 NA <NA> <NA> 0 27.58193304 27.58193304
## 527 NA <NA> <NA> 0 43.70029865 43.70029865
## 528 NA <NA> <NA> 1 48.41342464 48.41342464
## 529 NA <NA> <NA> 2 40.11503091 40.11503091
## 530 NA 1 1 NA NA NA
## 531 NA <NA> <NA> 0 36.34145256 36.34145256
## 532 NA <NA> <NA> 1 36.93878911 36.93878911
## 533 NA <NA> <NA> 0 44.09075458 44.09075458
## 534 NA <NA> <NA> 1 35.37832272 35.37832272
## 535 NA <NA> <NA> 0 29.74251309 29.74251309
## 536 NA <NA> <NA> 0 3.35552793 -3.35552793
## 537 NA <NA> <NA> 0 12.36080776 -12.36080776
## 538 NA <NA> <NA> 0 20.91981446 20.91981446
## 539 NA <NA> <NA> 0 17.19296761 17.19296761
## 540 NA <NA> <NA> 0 22.80529782 22.80529782
## 541 NA 1 1 3 37.85351828 37.85351828
## 542 10 <NA> <NA> 2 45.71810203 45.71810203
## 543 NA <NA> <NA> 0 39.18209087 39.18209087
## 544 NA 1 1 NA NA NA
## 545 NA <NA> <NA> 0 26.70297927 26.70297927
## 546 NA <NA> <NA> 0 37.59966070 -37.59966070
## 547 NA <NA> <NA> 1 25.79163463 -25.79163463
## 548 NA <NA> <NA> 1 23.04533937 23.04533937
## 549 NA <NA> <NA> 0 57.65008403 57.65008403
## 550 NA <NA> <NA> 2 52.88996636 52.88996636
## 551 NA <NA> <NA> 0 45.58619140 45.58619140
## 552 NA <NA> <NA> 0 55.98878309 55.98878309
## 553 NA <NA> <NA> 4 49.86941703 49.86941703
## 554 NA <NA> <NA> 0 39.27623486 39.27623486
## 555 NA <NA> <NA> 0 42.94065744 42.94065744
## 556 NA 2 0 7 8.73780415 8.73780415
## 557 NA 1 1 NA NA NA
## 558 NA 3 0 0 27.44343513 -27.44343513
## 559 NA <NA> <NA> 4 10.04267138 -10.04267138
## 560 NA <NA> <NA> 2 14.64779606 14.64779606
## 561 NA <NA> <NA> 3 18.95882990 -18.95882990
## 562 NA <NA> <NA> 0 42.65139375 42.65139375
## 563 NA <NA> <NA> 3 32.89681885 32.89681885
## 564 NA <NA> <NA> 3 30.44236219 30.44236219
## 565 NA <NA> <NA> 0 26.54462355 26.54462355
## 566 NA 2 0 5 9.90592018 9.90592018
## 567 NA <NA> <NA> 0 25.99966140 25.99966140
## 568 NA <NA> <NA> 0 37.06489832 37.06489832
## 569 NA 5 0 3 10.51720157 10.51720157
## 570 NA <NA> <NA> 1 8.83878791 8.83878791
## 571 NA <NA> <NA> 0 25.79163463 -25.79163463
## 572 NA 1 1 NA NA NA
## 573 6 2 0 0 NA NA
## 574 NA <NA> <NA> 0 3.32798888 3.32798888
## 575 NA 1 1 0 NA NA
## 576 NA <NA> <NA> 2 26.42720691 26.42720691
## 577 NA <NA> <NA> 2 19.07652737 19.07652737
## 578 NA 1 1 3 32.88369430 32.88369430
## 579 NA <NA> <NA> 6 8.79750942 8.79750942
## 580 NA <NA> <NA> 0 34.37660906 -34.37660906
## 581 NA <NA> <NA> 0 36.69836819 -36.69836819
## 582 NA <NA> <NA> 0 NA NA
## 583 NA 1 1 NA NA NA
## 584 NA 1 1 1 25.48651667 -25.48651667
## 585 NA <NA> <NA> 0 26.80239184 -26.80239184
## 586 NA <NA> <NA> 0 17.22991880 17.22991880
## 587 NA <NA> <NA> 2 16.99333532 16.99333532
## 588 NA 1 1 8 25.71605681 25.71605681
## 589 NA <NA> <NA> 4 27.34254024 27.34254024
## 590 NA 2 0 NA NA NA
## 591 NA <NA> <NA> 2 6.63149697 6.63149697
## 592 NA <NA> <NA> 1 28.89789088 -28.89789088
## 593 NA <NA> <NA> 4 6.66875068 -6.66875068
## 594 NA <NA> <NA> 0 19.70296898 -19.70296898
## 595 NA <NA> <NA> 0 27.77214475 27.77214475
## 596 NA <NA> <NA> 0 12.99390002 -12.99390002
## 597 NA <NA> <NA> 0 1.59710190 1.59710190
## 598 NA <NA> <NA> 3 4.90145755 -4.90145755
## 599 NA <NA> <NA> 4 2.59999035 -2.59999035
## 600 NA 1 1 3 4.25613314 4.25613314
## 601 NA <NA> <NA> 2 19.71369820 19.71369820
## 602 5 1 1 0 5.78049149 5.78049149
## 603 NA <NA> <NA> 7 1.22280551 1.22280551
## 604 NA 1 1 6 7.92125254 7.92125254
## 605 NA <NA> <NA> 0 32.17021086 -32.17021086
## 606 NA <NA> <NA> 0 34.81475557 -34.81475557
## 607 NA <NA> <NA> 0 31.45395160 -31.45395160
## 608 NA <NA> <NA> 0 25.79163463 -25.79163463
## 609 NA <NA> <NA> 0 25.79163463 -25.79163463
## 610 NA <NA> <NA> 0 31.74043124 -31.74043124
## 611 NA <NA> <NA> 0 32.17021086 -32.17021086
## 612 NA <NA> <NA> 0 34.71005178 -34.71005178
## 613 NA <NA> <NA> 0 25.46607155 -25.46607155
## 614 NA 1 1 1 31.79177941 31.79177941
## 615 NA 1 1 1 30.77954673 30.77954673
## 616 NA 2 0 0 34.66170169 34.66170169
## 617 NA 1 1 3 9.98521864 9.98521864
## 618 NA <NA> <NA> 1 34.64423126 34.64423126
## 619 NA <NA> <NA> 8 49.06747650 49.06747650
## 620 NA <NA> <NA> 1 39.98053909 39.98053909
## 621 NA <NA> <NA> 1 33.31893815 33.31893815
## 622 NA <NA> <NA> 3 38.73265964 38.73265964
## 623 NA <NA> <NA> 5 46.56016777 46.56016777
## 624 NA 3 0 4 5.43986796 5.43986796
## 625 NA <NA> <NA> 2 25.63312311 25.63312311
## 626 NA 1 1 8 0.28125397 0.28125397
## 627 NA 1 1 3 33.64704721 33.64704721
## 628 NA 3 0 3 35.37667204 -35.37667204
## 629 NA 3 0 7 12.35948341 12.35948341
## 630 NA <NA> <NA> 0 4.07106647 -4.07106647
## 631 NA <NA> <NA> 0 NA NA
## 632 NA <NA> <NA> 0 12.64409112 12.64409112
## 633 NA <NA> <NA> 0 34.29669616 34.29669616
## 634 NA <NA> <NA> 0 20.26898313 20.26898313
## 635 NA <NA> <NA> 1 31.09521025 31.09521025
## 636 NA 5 0 5 44.26742487 44.26742487
## 637 NA 1 1 1 42.18644320 -42.18644320
## 638 NA 1 1 1 44.02210596 -44.02210596
## 639 NA <NA> <NA> 4 25.78519056 25.78519056
## 640 NA 1 1 0 38.57756132 -38.57756132
## 641 NA <NA> <NA> 5 7.72459812 7.72459812
## 642 NA 2 0 NA NA NA
## 643 NA <NA> <NA> 1 11.74740395 11.74740395
## 644 NA <NA> <NA> 0 35.10328538 35.10328538
## 645 NA <NA> <NA> 0 NA NA
## 646 NA <NA> <NA> 0 NA NA
## 647 NA <NA> <NA> 0 37.01983418 37.01983418
## 648 NA <NA> <NA> 2 1.03652644 -1.03652644
## 649 NA <NA> <NA> 2 1.12232498 1.12232498
## 650 NA <NA> <NA> 2 1.48378641 1.48378641
## 651 NA <NA> <NA> 0 NA NA
## 652 NA <NA> <NA> 2 7.09600800 7.09600800
## 653 NA <NA> <NA> 0 NA NA
## 654 NA <NA> <NA> 0 NA NA
## 655 NA <NA> <NA> 0 12.83971200 12.83971200
## 656 NA <NA> <NA> 0 25.76023599 -25.76023599
## 657 NA <NA> <NA> 1 25.16284830 -25.16284830
## 658 NA 1 1 NA NA NA
## 659 NA <NA> <NA> 0 0.12535957 -0.12535957
## 660 NA <NA> <NA> 0 NA NA
## 661 NA <NA> <NA> 0 NA NA
## 662 NA <NA> <NA> 1 NA NA
## 663 NA <NA> <NA> 0 16.55564137 16.55564137
## 664 NA <NA> <NA> 0 26.80243548 -26.80243548
## 665 NA <NA> <NA> 1 25.48651667 -25.48651667
## 666 NA 2 0 4 10.39529783 10.39529783
## 667 NA <NA> <NA> 0 11.10780341 11.10780341
## 668 NA <NA> <NA> 3 39.67495457 39.67495457
## 669 NA 1 1 3 48.86736966 48.86736966
## 670 NA <NA> <NA> 1 40.23929028 40.23929028
## 671 NA <NA> <NA> 6 20.52628580 -20.52628580
## 672 NA <NA> <NA> 1 27.53376098 -27.53376098
## 673 NA <NA> <NA> 0 46.88768209 46.88768209
## 674 NA <NA> <NA> 3 7.28863437 -7.28863437
## 675 NA <NA> <NA> 1 47.26635450 47.26635450
## 676 NA <NA> <NA> 0 6.83057108 6.83057108
## 677 NA <NA> <NA> 1 45.89829828 45.89829828
## 678 NA <NA> <NA> 1 37.51986559 37.51986559
## 679 NA <NA> <NA> 0 34.10546659 34.10546659
## 680 8 <NA> <NA> 3 42.63744678 42.63744678
## 681 NA <NA> <NA> 3 46.74245057 46.74245057
## 682 NA <NA> <NA> 0 3.92614346 3.92614346
## 683 NA <NA> <NA> 0 42.26664486 42.26664486
## 684 NA <NA> <NA> 0 41.66077745 41.66077745
## 685 NA <NA> <NA> 0 39.72909208 39.72909208
## 686 NA <NA> <NA> 0 35.89738153 35.89738153
## 687 NA <NA> <NA> 0 16.46299407 -16.46299407
## 688 NA <NA> <NA> 3 40.42564479 40.42564479
## 689 NA <NA> <NA> 0 38.95373887 38.95373887
## 690 NA <NA> <NA> 0 0.75017422 0.75017422
## 691 NA <NA> <NA> 0 37.06337654 37.06337654
## 692 NA <NA> <NA> 0 41.66077745 41.66077745
## 693 NA <NA> <NA> 0 35.55338876 35.55338876
## 694 NA <NA> <NA> 0 35.86690149 35.86690149
## 695 NA <NA> <NA> 0 41.19535332 41.19535332
## 696 NA <NA> <NA> 0 5.38386362 5.38386362
## 697 NA <NA> <NA> 2 42.81116957 42.81116957
## 698 NA <NA> <NA> 2 38.74593397 38.74593397
## 699 NA 3 0 4 39.85261222 39.85261222
## 700 NA <NA> <NA> 0 41.66077745 41.66077745
## 701 NA <NA> <NA> 0 36.55123389 36.55123389
## 702 NA <NA> <NA> 2 39.12665103 39.12665103
## 703 NA <NA> <NA> 0 41.60963901 41.60963901
## 704 NA <NA> <NA> 0 39.44310870 39.44310870
## 705 NA <NA> <NA> 1 38.56370637 38.56370637
## 706 NA <NA> <NA> 2 45.14121498 45.14121498
## 707 NA <NA> <NA> 2 37.74679038 37.74679038
## 708 NA <NA> <NA> 0 41.64647681 41.64647681
## 709 NA <NA> <NA> 0 40.98117311 40.98117311
## 710 NA <NA> <NA> 0 35.28688776 35.28688776
## 711 NA <NA> <NA> 0 41.19535332 41.19535332
## 712 NA <NA> <NA> 1 37.34547043 37.34547043
## 713 NA <NA> <NA> 0 37.51432969 37.51432969
## 714 NA <NA> <NA> 0 42.88993222 42.88993222
## 715 NA <NA> <NA> 0 33.64322829 33.64322829
## 716 NA <NA> <NA> 0 40.31677478 40.31677478
## 717 NA <NA> <NA> 0 38.09975311 38.09975311
## 718 72 2 0 7 40.12460519 40.12460519
## 719 NA <NA> <NA> 1 3.81123699 -3.81123699
## 720 NA <NA> <NA> 0 45.85925832 45.85925832
## 721 NA 3 0 8 41.56482510 41.56482510
## 722 NA <NA> <NA> 4 39.56886028 39.56886028
## 723 NA <NA> <NA> 1 46.65877329 46.65877329
## 724 NA <NA> <NA> 0 6.23086329 6.23086329
## 725 NA <NA> <NA> 1 39.50421833 39.50421833
## 726 NA <NA> <NA> 0 27.04405009 27.04405009
## 727 NA <NA> <NA> 1 5.15251223 5.15251223
## 728 NA <NA> <NA> 0 3.96551634 3.96551634
## 729 NA <NA> <NA> 1 35.12159617 35.12159617
## 730 NA <NA> <NA> 0 39.58028659 39.58028659
## 731 NA <NA> <NA> 0 37.63878603 37.63878603
## 732 NA <NA> <NA> 2 37.70347598 37.70347598
## 733 NA <NA> <NA> 0 38.52351837 38.52351837
## 734 NA <NA> <NA> 1 42.77789671 42.77789671
## 735 NA <NA> <NA> 0 41.41517701 41.41517701
## 736 NA <NA> <NA> 0 37.88026930 37.88026930
## 737 NA <NA> <NA> 0 39.07788928 39.07788928
## 738 NA <NA> <NA> 0 38.77501787 38.77501787
## 739 NA <NA> <NA> 1 37.33372012 37.33372012
## 740 NA <NA> <NA> 1 2.04366440 2.04366440
## 741 NA <NA> <NA> 0 47.32604603 47.32604603
## 742 NA <NA> <NA> 0 39.51948825 39.51948825
## 743 NA <NA> <NA> 1 31.84253896 31.84253896
## 744 NA <NA> <NA> 1 30.09974272 30.09974272
## 745 NA <NA> <NA> 2 30.83723646 30.83723646
## 746 NA <NA> <NA> 4 NA NA
## 747 NA <NA> <NA> 0 37.68241100 37.68241100
## 748 NA <NA> <NA> 0 38.38409282 38.38409282
## 749 NA <NA> <NA> 2 29.27185970 29.27185970
## 750 NA <NA> <NA> 0 37.97305081 37.97305081
## 751 NA 1 1 6 37.52703143 37.52703143
## 752 NA <NA> <NA> 0 50.37284987 50.37284987
## 753 NA <NA> <NA> 1 11.47219786 11.47219786
## 754 NA <NA> <NA> 1 8.06949004 -8.06949004
## 755 NA <NA> <NA> 0 33.80589323 33.80589323
## 756 NA 1 1 2 47.31120259 47.31120259
## 757 NA <NA> <NA> 3 42.41501197 42.41501197
## 758 NA <NA> <NA> 2 38.38885688 38.38885688
## 759 NA <NA> <NA> 1 38.92581147 38.92581147
## 760 NA <NA> <NA> 1 47.25878122 47.25878122
## 761 15 1 1 5 45.91831254 45.91831254
## 762 NA <NA> <NA> 0 38.60172960 38.60172960
## 763 NA <NA> <NA> 4 42.00751036 42.00751036
## 764 10 1 1 4 25.65537016 -25.65537016
## 765 NA <NA> <NA> 1 45.12639523 45.12639523
## 766 10 1 1 4 36.75835276 36.75835276
## 767 NA <NA> <NA> 2 40.80149549 40.80149549
## 768 NA <NA> <NA> 1 43.37482171 43.37482171
## 769 NA <NA> <NA> 0 35.25005538 35.25005538
## 770 NA <NA> <NA> 2 41.26644544 41.26644544
## 771 NA <NA> <NA> 2 35.31470237 35.31470237
## 772 NA <NA> <NA> 3 41.95922051 41.95922051
## 773 NA <NA> <NA> 2 42.54681710 42.54681710
## 774 NA <NA> <NA> 1 39.62380702 39.62380702
## 775 NA <NA> <NA> 2 39.77698458 39.77698458
## 776 16 1 1 4 33.47215976 33.47215976
## 777 NA 1 1 NA NA NA
## 778 NA <NA> <NA> 3 42.96808331 42.96808331
## 779 3 1 1 2 42.24375010 42.24375010
## 780 NA <NA> <NA> 4 48.60652714 48.60652714
## 781 NA 1 1 4 39.40769423 39.40769423
## 782 NA 3 0 2 16.65164518 16.65164518
## 783 NA <NA> <NA> 2 7.99001409 7.99001409
## 784 NA <NA> <NA> 4 3.75145798 3.75145798
## 785 NA <NA> <NA> 3 6.94315476 6.94315476
## 786 9 3 0 4 16.41430090 16.41430090
## 787 NA 3 0 3 7.08178697 -7.08178697
## 788 NA <NA> <NA> 3 19.17627597 19.17627597
## 789 NA 4 0 5 0.09107861 0.09107861
## 790 NA 1 1 NA NA NA
## 791 NA 1 1 3 25.48651667 -25.48651667
## 792 NA <NA> <NA> 1 3.54859150 3.54859150
## 793 NA <NA> <NA> 5 32.30508668 32.30508668
## 794 NA <NA> <NA> 0 35.99240550 35.99240550
## 795 NA <NA> <NA> 5 29.23043211 29.23043211
## 796 NA <NA> <NA> 3 2.12954975 -2.12954975
## 797 NA <NA> <NA> 0 10.44864759 10.44864759
## ChromosomeCount PloidyLow diPloidyLow sfPloidy disfPloidy annual
## 1 22 2 0 2 0 0.00000000
## 2 26 2 0 2 0 0.00000000
## 3 26 2 0 2 0 0.00000000
## 4 26 2 0 2 0 0.00000000
## 5 26 2 0 2 0 0.00000000
## 6 26 2 0 2 0 0.00000000
## 7 26 2 0 2 0 0.00000000
## 8 26 2 0 2 0 0.00000000
## 9 26 2 0 2 0 0.00000000
## 10 26 2 0 2 0 0.00000000
## 11 26 2 0 2 0 0.00000000
## 12 26 2 0 2 0 0.00000000
## 13 26 2 0 2 0 0.00000000
## 14 26 2 0 2 0 0.00000000
## 15 26 2 0 2 0 0.00000000
## 16 52 4 1 4 1 0.00000000
## 17 26 2 0 2 0 0.00000000
## 18 26 2 0 2 0 0.00000000
## 19 26 2 0 2 0 0.00000000
## 20 26 2 0 2 0 0.00000000
## 21 26 2 0 2 0 0.00000000
## 22 26 2 0 2 0 0.00000000
## 23 26 2 0 2 0 0.00000000
## 24 26 2 0 2 0 0.00000000
## 25 40 3 1 3 1 0.00000000
## 26 52 4 1 4 1 0.00000000
## 27 26 2 0 2 0 0.00000000
## 28 52 4 1 4 1 0.00000000
## 29 26 2 0 2 0 0.00000000
## 30 52 4 1 4 1 0.00000000
## 31 52 4 1 4 1 0.00000000
## 32 26 2 0 2 0 0.00000000
## 33 26 2 0 2 0 0.00000000
## 34 26 2 0 2 0 0.00000000
## 35 26 2 0 2 0 0.00000000
## 36 26 2 0 2 0 0.00000000
## 37 26 2 0 2 0 0.00000000
## 38 26 2 0 2 0 0.00000000
## 39 26 2 0 2 0 0.00000000
## 40 26 2 0 2 0 0.00000000
## 41 52 4 1 4 1 0.00000000
## 42 26 2 0 2 0 0.00000000
## 43 38 3 1 3 1 0.00000000
## 44 26 2 0 2 0 0.00000000
## 45 26 2 0 2 0 0.00000000
## 46 26 2 0 2 0 0.00000000
## 47 26 2 0 2 0 0.00000000
## 48 26 2 0 2 0 0.00000000
## 49 52 4 1 4 1 0.00000000
## 50 26 2 0 2 0 0.00000000
## 51 26 2 0 2 0 0.00000000
## 52 104 8 1 8 1 0.00000000
## 53 26 2 0 2 0 0.00000000
## 54 26 2 0 2 0 0.00000000
## 55 26 2 0 2 0 0.00000000
## 56 26 2 0 2 0 0.00000000
## 57 26 2 0 2 0 0.00000000
## 58 78 6 1 6 1 0.00000000
## 59 26 2 0 2 0 0.00000000
## 60 26 2 0 2 0 0.00000000
## 61 26 2 0 2 0 0.00000000
## 62 52 4 1 4 1 0.00000000
## 63 12 NA <NA> 1 0 1.00000000
## 64 14 NA <NA> 1 0 1.00000000
## 65 14 NA <NA> 1 0 1.00000000
## 66 52 4 1 5 1 0.00000000
## 67 52 4 1 5 1 0.00000000
## 68 52 4 1 5 1 0.00000000
## 69 80 8 1 8 1 1.00000000
## 70 20 2 0 2 0 0.00000000
## 71 22 2 0 2 0 0.00000000
## 72 20 2 0 2 0 1.00000000
## 73 40 4 1 4 1 0.00000000
## 74 20 2 0 2 0 0.00000000
## 75 40 4 1 4 1 0.00000000
## 76 NA NA <NA> NA NA 0.00000000
## 77 20 2 0 2 0 0.00000000
## 78 20 2 0 2 0 0.00000000
## 79 40 4 1 4 1 1.00000000
## 80 26 2 0 2 0 0.00000000
## 81 26 2 0 2 0 0.00000000
## 82 26 2 0 2 0 0.00000000
## 83 26 2 0 2 0 0.00000000
## 84 26 2 0 2 0 0.00000000
## 85 26 2 0 2 0 0.00000000
## 86 16 2 0 2 0 0.00000000
## 87 38 NA <NA> 4 1 0.12393162
## 88 18 2 0 2 0 0.00000000
## 89 20 2 0 2 0 0.00000000
## 90 20 2 0 2 0 0.00000000
## 91 40 4 1 4 1 0.00000000
## 92 22 2 0 2 0 0.00000000
## 93 18 NA <NA> 2 0 0.00000000
## 94 18 NA <NA> 2 0 0.00000000
## 95 26 NA <NA> 2 0 0.00000000
## 96 NA NA <NA> NA NA 0.00000000
## 97 20 2 0 2 0 0.00000000
## 98 13 2 0 1 0 1.00000000
## 99 14 2 0 1 0 0.16666667
## 100 14 2 0 1 0 0.00000000
## 101 12 2 0 2 0 0.00000000
## 102 14 NA <NA> 1 0 1.00000000
## 103 16 NA <NA> 2 0 0.00000000
## 104 22 2 0 2 0 0.00000000
## 105 40 4 1 4 1 1.00000000
## 106 NA NA <NA> NA NA 0.00000000
## 107 48 4 1 5 1 0.00000000
## 108 18 3 1 2 0 0.00000000
## 109 18 3 1 2 0 0.00000000
## 110 18 3 1 2 0 0.00000000
## 111 32 4 1 3 1 0.00000000
## 112 22 3 1 2 0 0.00000000
## 113 16 2 0 2 0 0.00000000
## 114 16 2 0 2 0 0.00000000
## 115 30 4 1 3 1 1.00000000
## 116 16 2 0 2 0 0.00000000
## 117 64 8 1 6 1 0.00000000
## 118 32 4 1 3 1 0.00000000
## 119 16 2 0 2 0 1.00000000
## 120 24 3 1 2 0 0.00000000
## 121 16 2 0 2 0 0.00000000
## 122 22 3 1 2 0 0.00000000
## 123 24 3 1 2 0 0.00000000
## 124 22 3 1 2 0 0.00000000
## 125 28 4 1 3 1 0.00000000
## 126 16 2 0 2 0 0.00000000
## 127 22 3 1 2 0 0.17164179
## 128 16 2 0 2 0 0.00000000
## 129 16 2 0 2 0 0.00000000
## 130 24 3 1 2 0 0.00000000
## 131 24 3 1 2 0 0.00000000
## 132 16 2 0 2 0 0.00000000
## 133 16 2 0 2 0 1.00000000
## 134 16 2 0 2 0 0.00000000
## 135 16 2 0 2 0 0.00000000
## 136 46 4 1 4 1 0.00000000
## 137 18 1 0 2 0 0.00000000
## 138 18 1 0 2 0 0.00000000
## 139 18 1 0 2 0 0.00000000
## 140 18 1 0 2 0 0.00000000
## 141 28 2 0 4 1 0.00000000
## 142 20 NA <NA> 2 0 0.00000000
## 143 16 NA <NA> 2 0 0.00000000
## 144 16 1 0 2 0 0.00000000
## 145 18 2 0 2 0 0.00000000
## 146 18 NA <NA> 2 0 0.00000000
## 147 20 2 0 2 0 0.00000000
## 148 18 NA <NA> 2 0 0.00000000
## 149 22 2 0 2 0 0.00000000
## 150 22 2 0 2 0 0.00000000
## 151 16 2 0 1 0 0.00000000
## 152 19 2 0 1 0 0.00000000
## 153 18 2 0 2 0 0.00000000
## 154 22 2 0 2 0 0.00000000
## 155 22 NA <NA> 2 0 0.00000000
## 156 22 2 0 2 0 0.00000000
## 157 22 2 0 2 0 0.00000000
## 158 22 2 0 2 0 0.00000000
## 159 22 2 0 2 0 0.00000000
## 160 16 2 0 2 0 0.00000000
## 161 16 2 0 2 0 0.00000000
## 162 16 2 0 2 0 0.00000000
## 163 32 2 0 3 1 0.00000000
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## disfPloidy_corrected NewPloidy
## 1 0 0
## 2 0 0
## 3 0 0
## 4 0 0
## 5 0 0
## 6 0 0
## 7 0 0
## 8 0 0
## 9 0 0
## 10 0 0
## 11 0 0
## 12 0 0
## 13 0 0
## 14 0 0
## 15 0 0
## 16 1 1
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## 797 0 0# Run pgls and allow lambda to vary
model_sub_sym<-gls(log10(Num_Introduced + 1) ~ NewPloidy + AbsLatNative + areaNativeScale + Human_Uses + annual, data=ploidy_data_sym, correlation=corPagel(value=0, phy=pruned, fixed=FALSE, form=~"Species"), method = "ML", na.action=na.exclude)
# Inspect model fit
plot(model_sub_sym)
qqnorm(resid(model_sub_sym))
qqline(resid(model_sub_sym))
# Test for significance
summary(model_sub_sym)## Generalized least squares fit by maximum likelihood
## Model: log10(Num_Introduced + 1) ~ NewPloidy + AbsLatNative + areaNativeScale + Human_Uses + annual
## Data: ploidy_data_sym
## AIC BIC logLik
## 565.1794 602.0865 -274.5897
##
## Correlation Structure: corPagel
## Formula: ~"Species"
## Parameter estimate(s):
## lambda
## 0.04302553
##
## Coefficients:
## Value Std.Error t-value p-value
## (Intercept) 0.15348134 0.04767661 3.219216 0.0013
## NewPloidy1 0.00720020 0.02873715 0.250554 0.8022
## AbsLatNative -0.00253587 0.00093606 -2.709093 0.0069
## areaNativeScale -0.05149200 0.01194693 -4.310060 0.0000
## Human_Uses 0.19459881 0.00720993 26.990371 0.0000
## annual 0.08798791 0.03263117 2.696437 0.0072
##
## Correlation:
## (Intr) NwPld1 AbsLtN arNtvS Hmn_Us
## NewPloidy1 -0.135
## AbsLatNative -0.517 -0.071
## areaNativeScale 0.018 -0.044 0.103
## Human_Uses -0.269 0.062 0.077 -0.377
## annual -0.070 -0.044 -0.093 -0.040 0.074
##
## Standardized residuals:
## Min Q1 Med Q3 Max
## -3.2873233 -0.5202143 -0.2629220 0.5746847 3.4055491
##
## Residual standard error: 0.3531637
## Degrees of freedom: 745 total; 739 residualAnova(model_sub_sym, type=2, contrasts=list(topic=contr.sum))## Analysis of Deviance Table (Type II tests)
##
## Response: log10(Num_Introduced + 1)
## Df Chisq Pr(>Chisq)
## NewPloidy 1 0.0628 0.802159
## AbsLatNative 1 7.3392 0.006747 **
## areaNativeScale 1 18.5766 1.632e-05 ***
## Human_Uses 1 728.4801 < 2.2e-16 ***
## annual 1 7.2708 0.007009 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Plotting the results
Raw genus+subfamily level data
Here we plot the means and standard error calculated from the raw data in the expanded dataset (more data points in each category).
# Prep the data for plotting
ploidy_sub_sum<- ploidy_data1 %>%
filter(!is.na(Fixer) & !is.na(NewPloidy)) %>%
dplyr::group_by(NewPloidy, Fixer) %>%
dplyr::summarise(mean=mean(Num_Introduced), se=std.error(Num_Introduced))## `summarise()` has grouped output by 'NewPloidy'. You can override using the `.groups` argument.# Reaction norm plot
sub_interaction<-ggplot(ploidy_sub_sum, aes(x=Fixer, y=mean, fill=NewPloidy)) +
geom_errorbar(aes(ymin=mean-se, ymax=mean+se), width=0.1, position=position_dodge(0.2)) +
geom_line(aes(group=NewPloidy), position=position_dodge(0.2)) +
geom_point(pch =21, size=4, position=position_dodge(0.2)) +
(ylab("Introduced ranges (no.)")) +
(xlab("Symbiotic state")) +
# scale_fill_manual(name="", labels=c("Diploid", "Polyploid"), values=ploidy_colours[c(6,4)]) +
scale_x_discrete(labels=c("1" = "Symbiotic", "0" = "Non-symbiotic"), limits=c("1", "0")) +
theme_classic() +
theme(axis.title.x = element_text(size=13),
axis.title.y = element_text(size=13),
axis.text.y= element_text(size=12),
axis.text.x= element_text(size=12),
legend.title= element_text(size=12),
legend.text=element_text(size=12),
legend.position="top")
# Prep data for specificity on rhizobia
ploidy_sub_spec<- ploidy_data1 %>%
filter(!is.na(Specialist) & !is.na(NewPloidy)) %>%
dplyr::group_by(NewPloidy, Specialist) %>%
dplyr::summarise(mean=mean(Num_Introduced), se=std.error(Num_Introduced))## `summarise()` has grouped output by 'NewPloidy'. You can override using the `.groups` argument.# Reaction norm for specificity
sub_spec<-ggplot(ploidy_sub_spec, aes(x=Specialist, y=mean, fill=NewPloidy)) +
geom_errorbar(aes(ymin=mean-se, ymax=mean+se), width=0.1, position=position_dodge(0.2)) +
geom_line(aes(group=NewPloidy), position=position_dodge(0.2)) +
geom_point(pch =21, size=4, position=position_dodge(0.2)) +
(ylab("Introduced ranges (no.)")) +
(xlab("Specificity on rhizobia")) +
# scale_fill_manual(name="", labels=c("Diploid", "Polyploid"), values=ploidy_colours[c(6,4)]) +
scale_x_discrete(labels=c("1" = "Specialist", "0" = "Generalist"), limits=c("1", "0")) +
theme_classic() +
theme(axis.title.x = element_text(size=13),
axis.title.y = element_text(size=13),
axis.text.y= element_text(size=12),
axis.text.x= element_text(size=12),
legend.title= element_text(size=12),
legend.text=element_text(size=12),
legend.position="top")
# Combine the two plots
Figure_sub <- ggarrange(sub_interaction, sub_spec,
labels=c("a", "b"),
ncol = 2, nrow=1,
common.legend=TRUE,
legend = "top")
Figure_sub
PGLS interaction of ploidy and symbiosis
The means and standard deviation plotted here are output from the pgls models in our analyses.
# Prep the output from the model
model_sub2_results <- model_sub2_results %>%
mutate(NewPloidy=as.factor(NewPloidy)) %>%
mutate(Fixer=as.factor(Fixer))
model_sub2_results## NewPloidy Fixer lsmean SE df lower.CL upper.CL
## 1 0 0 0.3983174 0.06943741 801 0.2620166 0.5346181
## 2 1 0 0.5269398 0.08509955 801 0.3598953 0.6939843
## 3 0 1 0.4003653 0.04041725 801 0.3210291 0.4797015
## 4 1 1 0.4112109 0.04564199 801 0.3216188 0.5008029# Plot the means
sub_interaction2<-ggplot(model_sub2_results, aes(x=Fixer, y=lsmean, fill=NewPloidy)) +
geom_errorbar(aes(ymin=lsmean-SE, ymax=lsmean+SE), width=0.1, position=position_dodge(0.2)) +
geom_line(aes(group=NewPloidy), position=position_dodge(0.2)) +
geom_point(pch =21, size=4, position=position_dodge(0.2)) +
(ylab("Introduced ranges (log)")) +
(xlab("Symbiotic state")) +
# scale_fill_manual(name="", labels=c("Diploid", "Polyploid"), values=ploidy_colours[c(6,4)]) +
scale_x_discrete(labels=c("1" = "Symbiotic", "0" = "Non-symbiotic"), limits=c("1", "0")) +
theme_classic() +
theme(axis.title.x = element_text(size=13),
axis.title.y = element_text(size=13),
axis.text.y= element_text(size=12),
axis.text.x= element_text(size=12),
legend.title= element_text(size=12),
legend.text=element_text(size=12),
legend.position="top")
# Prep the output from the model
model_sub_spec2_results <- model_sub_spec2_results %>%
mutate(NewPloidy=as.factor(NewPloidy)) %>%
mutate(Specialist=as.factor(Specialist))
# Plot the model means
sub_spec2<-ggplot(model_sub_spec2_results, aes(x=Specialist, y=lsmean, fill=NewPloidy)) +
geom_errorbar(aes(ymin=lsmean-SE, ymax=lsmean+SE), width=0.1, position=position_dodge(0.2)) +
geom_line(aes(group=NewPloidy), position=position_dodge(0.2)) +
geom_point(pch =21, size=4, position=position_dodge(0.2)) +
(ylab("Introduced ranges (log)")) +
(xlab("Specificity on rhizobia")) +
# scale_fill_manual(name="", labels=c("Diploid", "Polyploid"), values=ploidy_colours[c(6,4)]) +
scale_x_discrete(labels=c("1" = "Specialist", "0" = "Generalist"), limits=c("1", "0")) +
theme_classic() +
theme(axis.title.x = element_text(size=13),
axis.title.y = element_text(size=13),
axis.text.y= element_text(size=12),
axis.text.x= element_text(size=12),
legend.title= element_text(size=12),
legend.text=element_text(size=12),
legend.position="top")
# Combine the plots
Figure_sub2 <- ggarrange(sub_interaction2, sub_spec2,
labels=c("a", "b"),
ncol = 2, nrow=1,
common.legend=TRUE,
legend = "top")
Figure_sub2
Plot symbiotic and non-symbiotic results separately
Here we are plotting the raw data for just the symbiotic species and just the non-symbiotic species.
# Plot just the non-symbiotic species
non_plot<-ploidy_data1 %>%
filter(Fixer==0) %>%
ggplot(aes(x=NewPloidy, y=log(Num_Introduced+1), fill=NewPloidy)) +
geom_boxplot(colour="grey42") +
theme_classic() +
(ylab("Introduced ranges (log)")) +
(xlab("Ploidy level")) +
scale_x_discrete(labels=c("1" = "Polyploid", "0" = "Diploid"), limits=c("1", "0")) +
# scale_fill_manual(values=ploidy_colours[c(6,4)]) +
theme(axis.title.x = element_text(size=13),
axis.title.y = element_text(size=13),
axis.text.y= element_text(size=12),
axis.text.x= element_text(size=12),
legend.title= element_text(size=12),
legend.text=element_text(size=12),
legend.position="none")
non_plot
# Plot just the symbiotic species
sym_plot<-ploidy_data1 %>%
filter(Fixer==1) %>%
ggplot(aes(x=NewPloidy, y=log(Num_Introduced+1), fill=NewPloidy)) +
geom_boxplot(colour="grey42") +
theme_classic() +
(ylab("Introduced ranges (log)")) +
(xlab("Ploidy level")) +
scale_x_discrete(labels=c("1" = "Polyploid", "0" = "Diploid"), limits=c("1", "0")) +
# scale_fill_manual(values=ploidy_colours[c(6,4)]) +
theme(axis.title.x = element_text(size=13),
axis.title.y = element_text(size=13),
axis.text.y= element_text(size=12),
axis.text.x= element_text(size=12),
legend.title= element_text(size=12),
legend.text=element_text(size=12),
legend.position="none")
sym_plot## Warning: Removed 26 rows containing missing values (stat_boxplot).
# Combine the plots for supplemental file
Figure_supp <- ggarrange(non_plot, sym_plot,
labels=c("a", "b"),
ncol = 2, nrow=1,
common.legend=TRUE,
legend = "none")## Warning: Removed 26 rows containing missing values (stat_boxplot).
## Warning: Removed 26 rows containing missing values (stat_boxplot).Figure_supp